ON SOME ASPECTS OF CLUSTER SAMPLING
|
|
- Baldwin Norris
- 7 years ago
- Views:
Transcription
1 O O APT OF LUTR APLIG PRAJIT PAL.c. (Agrcultural tatstcs, Roll o. 446 I.A..R.I., Lbrary Aveue, ew Delh- harperso: Dr. U.. ud Abstract: luster saplg s a procedure fro e populato of partcular cluster (a group of saplg uts sze we draw e saple by RWOR of at sze. It s used whe e lst of uts s ot avalable. A saplg procedure uequal cluster saplg for fxed saple sze, e uber of uts e tal saple of selected clusters exceeds e plaed sze of uts s dscussed. A schee for dscardg e excess uber of clusters fro e tal saple of clusters s also preseted. Ths procedure, takg to accout splcty ad practcal feasblty, ca be used practce u-stage uequal cluster saplg desgs for arrvg at e fxed saple sze of eleets. The reducto e varace effcecy of estator o accout of e decrease e saple sze copared to at of e tally selected usual u-stage uequal cluster saple of a relatvely larger sze s copesated by ts creased cost effcecy. Key words: luster aplg, luster, ffcecy, aple ze.. Itroducto I rado saplg, t s presued at e populato has bee dvded to a fte uber of dstct ad detfable uts defed as saplg uts. The sallest ut to whch e populato ca be dvded s called a eleet of e populato. A group of such eleets s kow as a cluster. Whe he saplg ut s a cluster, e procedure s called cluster saplg. If e etre area cotag e populato uder study s dvded to saller segets ad each eleet e populato belogs to oe ad oly oe seget, e procedure s soetes called area saplg. Geerally, detfcato ad locato of a eleet requres cosderable te. However, oce a eleet has bee located, e te take for surveyg a few eghborg eleets s sall. Thus, e a fucto cluster saplg s to specfy clusters or to dvde e populato to approprate clusters. lusters are geerally ade up of eghborg eleets ad, erefore, e eleets w a cluster ted to have slar characterstcs. As a sple rule, e uber of eleets a cluster should be sall ad e uber of clusters should be large. After dvdg e populato to specfed clusters, e requred uber of clusters ca be selected eer by equal or uequal probabltes of selecto. All e eleets selected clusters are e euerated. For a gve uber of saplg uts, cluster saplg s ore coveet ad less costly. The advatages of cluster saplg are at, ollecto of data for eghborg eleets s easer, cheaper, faster ad operatoally ore coveet a observg uts spread over a rego. It s less costly a sple rado saplg due to e savg of te joureys, detfcato, cotacts, etc.
2 O oe Aspects of luster aplg Whe e saplg frae of eleets ay ot be readly avalable whch s e geerally e case large scale surveys. The dsadvatage of t s at e effcecy of cluster saplg relatve to sple rado saplg s less. For ay types of populatos a lst of uts (eleets s ot avalable, for e.g. to estate e dstrct crop yeld e lst of dvdual farers s ot avalable we use cluster saplg. The eod of cluster or area saplg s applcable such cases. However, w clusters of uequal szes, e uber of uts to be ultately observed s ot uder cotrol. Ths ay result e uber of uts to be observed beg uch larger a plaed, leadg to operatoal dffcultes, partcularly whe ere are budgetary, traed apower ad oer costrats. I e usual cluster saplg, e uber of clusters s fxed ad e uber of uts s a varable whe clusters are uequal. But soe stuatos deeper observato of uts volvg use of sophstcated struets ad costly cosuable ateral s volved, t ay be desrable to fx e uber of eleets advace. I agrcultural surveys households are uts, soetes reuerato s pad to e selected households as a otvato to provde better qualty of data. I such stuatos t would be desrable to keep e ultate saple sze of uts to be observed, a far as possble, close to e plaed sze. Oe possble approach to s proble would be to dscard a sub-saple of clusters fro e tally selected clusters w a sutable procedure whch would, as far as possble, esure e requred saple sze of uts wout coplcatg e desg ad retag e ubased character of e estator. The procedures for dscardg e excess uber of clusters fro aogst e tally selected clusters ad for e cosequet estato of populato paraeters are dscussed. xaple.: To estate e wheat producto a dstrct cotag te blocks a group of ree vllages ca be fored as a cluster. ow saple of ree blocks are take at rado ad used to estate e wheat producto. otatos We shall assue at ( e populato cossts of clusters of eleets each ad ( clusters are selected fro clusters by sple rado saplg wout replaceet. Let, j be e value of e characterstc uder study for e j eleet e cluster, j,,, ;,,,. j, e ea per eleet of e cluster j., e ea of cluster eas j, e populato ea j (j., e ea square betwee eleets e cluster j
3 O oe Aspects of luster aplg w b (., e ea square w clusters, e ea square betwee cluster eas As a estator of, cosder e ea of cluster eas e saple, aely, y y. learly, y s a ubased estator of, w ts varace gve by V(y b ce, (s b ( y. y b A ubased estator of ( y V V(y ( s b ffcecy of luster aplg V(y R V(y b b s. The Proble I practcal stuato we ay get e clusters of uequal szes. Let e populato be coposed of clusters, e cluster cosstg of eleets (, ad at a saple of clusters s draw fro t by e eod of sple rado saplg wout replaceet. Furer, let us deote by e average cluster sze e populato, by e uber of eleets e selected clusters, by e saple average cluster sze ad e plaed uber of eleets to be fally observed e saple. As per e pla, has already bee selected ad t s assued at s greater a. Hece, e proble s ow to work out e approxate uber of clusters to be
4 O oe Aspects of luster aplg rejected so at e uber of eleets of e tally selected clusters ad e plaed sze of uts, by e average cluster sze e populato. Thus, e approxate uber of clusters to be rejected fro e tally elected clusters would be gve by (say If s a fracto, t s approxated to e ext lower teger. Havg worked out e approxate uber of clusters for rejecto aely, we select clusters fro e tally selected clusters by e eod of sple rado saplg wout replaceet ad reject e fro e. Let e uber of clusters fally selected, by rejectg clusters fro e tally selected clusters be deoted by. learly ad are rado varables. To fd e approxate uber of clusters to be rejected, alteratvely e average cluster sze based o e saple, at s, ay also be used. The approxate uber of clusters to be rejected s case would be gve by (say Here too, ad are rado varables as well as. A rd alteratve would be to estate e average cluster sze fro a larger saple of e populato wout apprecably addg to e cost of equry ad utlze t for deterg e uber of clusters for rejecto. tll aoer approach would be to select a cluster fro e tally selected clusters ad rejectg e tll as close to e plaed uber of uts. I e followg sectos, e procedures for estato of populato paraeters based o e frst two schees suggested above for dscardg e excess uber of clusters has bee descrbed.. stato of Populato Total whe e Average luster ze e Populato s Kow The proposed estator of, e populato total for e study character y, s gve by Ŷ (., y j j y j deotg e j eleet of e cluster. Ŷ s evdetly a ubased estator for. The varace of e estator Ŷ s gve by V(Ŷ ( 4
5 O oe Aspects of luster aplg (. ad j y j The expectato of requred e above equato ay be obtaed to a secod order of approxato utlzg e usual techque as follows: (( ( ( ( ad ( ( Hece a expresso for up to e order of s gve by Therefore, (Ŷ V (. The secod ter e varace expresso at (. above s postve ad us t shows e crease varace due to rejecto of clusters over at of u-stage uequal cluster saplg w o rejecto of clusters. 5
6 O oe Aspects of luster aplg A ubased estator of e varace (. s gve by s (Ŷ Vˆ (.4 s 4. stato of e Populato Total whe Average luster ze e Populato s ot Kow A ubased estator of, e populato total for e study character y, s gve by Ŷ (4. s as defed earler ad ts varace s gve by s ( (Ŷ Vˆ (4. ( ( (4. ow (, ad proceedg e sae way as above, e expected value of s obtaed. ubsttutg e above equato we get ( [ / σ ] (4.4 σ ad also ( To obta e expected value of, we proceed e sae way as above ad substtutg e above equato we get, ( σ ( (4.5 Fro equatos (4., (4.4 ad (4.5, we obta 6
7 O oe Aspects of luster aplg σ σ Thus, e varace of e estator s gve by Ŷ (Ŷ V (4.6 s as defed earler. The varace expresso at (4.6 above dcates at f e uber of clusters to be rejected s based o average cluster sze as obtaed fro e saple, ere s a reducto e varace as copared to e stuato whe e average cluster sze s based o e etre populato. A ubased estator of e varace preseted at (4. s gve b s (Ŷ Vˆ (4.7 s as defed uder (.4. s 5. Relatve ffcecy of e uggested Procedure Let deote e varace correspodg to procedure descrbed ad usual cluster saplg procedure respectvely. We defe relatve varace effcecy (RV of e descrbed procedure over e usual procedure as RV V ad V V V. osder e cost fucto as s e cost of e survey apart fro e overhead cost of plag ad aalyss. s e cost per cluster for prelary operatos, such as, jourey, detfcato, cotact, etc.volved coductg e survey a cluster ad s e cost of surveyg oe ut. I geeral s expected to be cosderably less a. However, certa cases ay be large, partcularly whe observatos o e uts su able ateral ad us s lkely to be suffcetly ore a. The relatve cost effcecy of e suggested procedure over e usual cluster saplg procedure s defed as R e suggested procedure uder xpected cos t e usual cluster saplg procedure uder xpected cos t 7
8 O oe Aspects of luster aplg Ad, e preset stuato, e R of e suggested procedure whe e average cluster sze s based o e etre populato over e usual cluster saplg procedure s. However, whe e average cluster sze s estated fro e saple e R of e suggested procedure over e usual cluster saplg procedure reduces to It s see at R (% of e suggested procedure bo e cases wll be ore a. 6. prcal Illustrato To deostrate e usefuless of e suggested saplg procedure, uercal llustrato s preseted. For s purpose, a populato of clusters a tehsl s take. The eleets of e clusters were holdgs of varyg szes ad e character uder study beg area uder wheat crop uts of oe-te of a hectare durg e rab seaso. It s desred to estate e area uder wheat crop e tehsl fro a saple of 5 clusters, subject to e codto at e saple selected clusters should ot cota ore a 5 holdgs. A saple of 5 clusters usg sple rado saplg wout replaceet s draw ad e total uber of holdgs costtutg e 5 clusters was 58. Hece order to be close to e plaed sze e populato was 4. ad at estated fro e saple of 5 clusters was.9. Followg e procedure dscussed above, e uber of clusters to be dscarded worked out to uder each of e two cases. The total uber of holdgs e fally selected clusters, after rejectg e clusters fro e tally selected 5 cluster was 48, whch was close to e plaed sze. The estate of total ad ts varace as well as e relatve varace effcecy ad relatve cost effcecy of e proposed estators over e usual procedure, are preseted e followg table. Usual procedure uggested procedure Ŷ V (Ŷ Relatve Varace ffcecy (% Relatve ost ffcecy (% Average cluster sze kow Average cluster sze estated Thus, as expected, because of e reducto of e saple sze uder e suggested techque copared to e usual procedure, e proposed estator s less effcet a e usual procedure. O e oer had e suggested procedure s ore effcet a e 8
9 O oe Aspects of luster aplg usual procedure fro cost effcecy pot of vew. Thus, e suggested techque esures achevg e plaed sze of e saple ad e reducto ts varace effcecy s copesated by ts creased cost effcecy. Refereces ochra, W.G. (977. aplg techques rd d. (ew ork, Joh Wley. ukhate, P.V. ad ukhate, B.V. (97. aplg Theory of urveys w Applcatos, d d, Ida ocety of Agrcultural tatstcs, ew Delh-. P..ehrotra (987. O uequal cluster saplg for fxed saple sze The tatstca, 6,
Numerical Comparisons of Quality Control Charts for Variables
Global Vrtual Coferece Aprl, 8. - 2. 203 Nuercal Coparsos of Qualty Cotrol Charts for Varables J.F. Muñoz-Rosas, M.N. Pérez-Aróstegu Uversty of Graada Facultad de Cecas Ecoócas y Epresarales Graada, pa
More informationA Study of Unrelated Parallel-Machine Scheduling with Deteriorating Maintenance Activities to Minimize the Total Completion Time
Joural of Na Ka, Vol. 0, No., pp.5-9 (20) 5 A Study of Urelated Parallel-Mache Schedulg wth Deteroratg Mateace Actvtes to Mze the Total Copleto Te Suh-Jeq Yag, Ja-Yuar Guo, Hs-Tao Lee Departet of Idustral
More informationOnline Appendix: Measured Aggregate Gains from International Trade
Ole Appedx: Measured Aggregate Gas from Iteratoal Trade Arel Burste UCLA ad NBER Javer Cravo Uversty of Mchga March 3, 2014 I ths ole appedx we derve addtoal results dscussed the paper. I the frst secto,
More informationSTATISTICAL PROPERTIES OF LEAST SQUARES ESTIMATORS. x, where. = y - ˆ " 1
STATISTICAL PROPERTIES OF LEAST SQUARES ESTIMATORS Recall Assumpto E(Y x) η 0 + η x (lear codtoal mea fucto) Data (x, y ), (x 2, y 2 ),, (x, y ) Least squares estmator ˆ E (Y x) ˆ " 0 + ˆ " x, where ˆ
More informationIDENTIFICATION OF THE DYNAMICS OF THE GOOGLE S RANKING ALGORITHM. A. Khaki Sedigh, Mehdi Roudaki
IDENIFICAION OF HE DYNAMICS OF HE GOOGLE S RANKING ALGORIHM A. Khak Sedgh, Mehd Roudak Cotrol Dvso, Departmet of Electrcal Egeerg, K.N.oos Uversty of echology P. O. Box: 16315-1355, ehra, Ira sedgh@eetd.ktu.ac.r,
More informationAPPENDIX III THE ENVELOPE PROPERTY
Apped III APPENDIX III THE ENVELOPE PROPERTY Optmzato mposes a very strog structure o the problem cosdered Ths s the reaso why eoclasscal ecoomcs whch assumes optmzg behavour has bee the most successful
More informationAbraham Zaks. Technion I.I.T. Haifa ISRAEL. and. University of Haifa, Haifa ISRAEL. Abstract
Preset Value of Autes Uder Radom Rates of Iterest By Abraham Zas Techo I.I.T. Hafa ISRAEL ad Uversty of Hafa, Hafa ISRAEL Abstract Some attempts were made to evaluate the future value (FV) of the expected
More informationANOVA Notes Page 1. Analysis of Variance for a One-Way Classification of Data
ANOVA Notes Page Aalss of Varace for a Oe-Wa Classfcato of Data Cosder a sgle factor or treatmet doe at levels (e, there are,, 3, dfferet varatos o the prescrbed treatmet) Wth a gve treatmet level there
More information6.7 Network analysis. 6.7.1 Introduction. References - Network analysis. Topological analysis
6.7 Network aalyss Le data that explctly store topologcal formato are called etwork data. Besdes spatal operatos, several methods of spatal aalyss are applcable to etwork data. Fgure: Network data Refereces
More information1. The Time Value of Money
Corporate Face [00-0345]. The Tme Value of Moey. Compoudg ad Dscoutg Captalzato (compoudg, fdg future values) s a process of movg a value forward tme. It yelds the future value gve the relevat compoudg
More informationChapter 3. AMORTIZATION OF LOAN. SINKING FUNDS R =
Chapter 3. AMORTIZATION OF LOAN. SINKING FUNDS Objectves of the Topc: Beg able to formalse ad solve practcal ad mathematcal problems, whch the subjects of loa amortsato ad maagemet of cumulatve fuds are
More informationof the relationship between time and the value of money.
TIME AND THE VALUE OF MONEY Most agrbusess maagers are famlar wth the terms compoudg, dscoutg, auty, ad captalzato. That s, most agrbusess maagers have a tutve uderstadg that each term mples some relatoshp
More informationThe analysis of annuities relies on the formula for geometric sums: r k = rn+1 1 r 1. (2.1) k=0
Chapter 2 Autes ad loas A auty s a sequece of paymets wth fxed frequecy. The term auty orgally referred to aual paymets (hece the ame), but t s ow also used for paymets wth ay frequecy. Autes appear may
More informationSHAPIRO-WILK TEST FOR NORMALITY WITH KNOWN MEAN
SHAPIRO-WILK TEST FOR NORMALITY WITH KNOWN MEAN Wojcech Zelńsk Departmet of Ecoometrcs ad Statstcs Warsaw Uversty of Lfe Sceces Nowoursyowska 66, -787 Warszawa e-mal: wojtekzelsk@statystykafo Zofa Hausz,
More informationNumerical Methods with MS Excel
TMME, vol4, o.1, p.84 Numercal Methods wth MS Excel M. El-Gebely & B. Yushau 1 Departmet of Mathematcal Sceces Kg Fahd Uversty of Petroleum & Merals. Dhahra, Saud Araba. Abstract: I ths ote we show how
More informationADAPTATION OF SHAPIRO-WILK TEST TO THE CASE OF KNOWN MEAN
Colloquum Bometrcum 4 ADAPTATION OF SHAPIRO-WILK TEST TO THE CASE OF KNOWN MEAN Zofa Hausz, Joaa Tarasńska Departmet of Appled Mathematcs ad Computer Scece Uversty of Lfe Sceces Lubl Akademcka 3, -95 Lubl
More informationChapter 3 0.06 = 3000 ( 1.015 ( 1 ) Present Value of an Annuity. Section 4 Present Value of an Annuity; Amortization
Chapter 3 Mathematcs of Face Secto 4 Preset Value of a Auty; Amortzato Preset Value of a Auty I ths secto, we wll address the problem of determg the amout that should be deposted to a accout ow at a gve
More informationSimple Linear Regression
Smple Lear Regresso Regresso equato a equato that descrbes the average relatoshp betwee a respose (depedet) ad a eplaator (depedet) varable. 6 8 Slope-tercept equato for a le m b (,6) slope. (,) 6 6 8
More informationAn Effectiveness of Integrated Portfolio in Bancassurance
A Effectveess of Itegrated Portfolo Bacassurace Taea Karya Research Ceter for Facal Egeerg Isttute of Ecoomc Research Kyoto versty Sayouu Kyoto 606-850 Japa arya@eryoto-uacp Itroducto As s well ow the
More informationPreprocess a planar map S. Given a query point p, report the face of S containing p. Goal: O(n)-size data structure that enables O(log n) query time.
Computatoal Geometry Chapter 6 Pot Locato 1 Problem Defto Preprocess a plaar map S. Gve a query pot p, report the face of S cotag p. S Goal: O()-sze data structure that eables O(log ) query tme. C p E
More informationA Fast Clustering Algorithm to Cluster Very Large Categorical Data Sets in Data Mining
A Fast Clusterg Algorth to Cluster Very Large Categorcal Data Sets Data Mg Zhexue Huag * Cooperatve Research Cetre for Advaced Coputatoal Systes CSIRO Matheatcal ad Iforato Sceces GPO Box 664, Caberra
More informationFractal-Structured Karatsuba`s Algorithm for Binary Field Multiplication: FK
Fractal-Structured Karatsuba`s Algorthm for Bary Feld Multplcato: FK *The authors are worg at the Isttute of Mathematcs The Academy of Sceces of DPR Korea. **Address : U Jog dstrct Kwahadog Number Pyogyag
More informationThe Gompertz-Makeham distribution. Fredrik Norström. Supervisor: Yuri Belyaev
The Gompertz-Makeham dstrbuto by Fredrk Norström Master s thess Mathematcal Statstcs, Umeå Uversty, 997 Supervsor: Yur Belyaev Abstract Ths work s about the Gompertz-Makeham dstrbuto. The dstrbuto has
More informationANNEX 77 FINANCE MANAGEMENT. (Working material) Chief Actuary Prof. Gaida Pettere BTA INSURANCE COMPANY SE
ANNEX 77 FINANCE MANAGEMENT (Workg materal) Chef Actuary Prof. Gada Pettere BTA INSURANCE COMPANY SE 1 FUNDAMENTALS of INVESTMENT I THEORY OF INTEREST RATES 1.1 ACCUMULATION Iterest may be regarded as
More informationOptimal multi-degree reduction of Bézier curves with constraints of endpoints continuity
Computer Aded Geometrc Desg 19 (2002 365 377 wwwelsevercom/locate/comad Optmal mult-degree reducto of Bézer curves wth costrats of edpots cotuty Guo-Dog Che, Guo-J Wag State Key Laboratory of CAD&CG, Isttute
More informationAverage Price Ratios
Average Prce Ratos Morgstar Methodology Paper August 3, 2005 2005 Morgstar, Ic. All rghts reserved. The formato ths documet s the property of Morgstar, Ic. Reproducto or trascrpto by ay meas, whole or
More informationCH. V ME256 STATICS Center of Gravity, Centroid, and Moment of Inertia CENTER OF GRAVITY AND CENTROID
CH. ME56 STTICS Ceter of Gravt, Cetrod, ad Momet of Ierta CENTE OF GITY ND CENTOID 5. CENTE OF GITY ND CENTE OF MSS FO SYSTEM OF PTICES Ceter of Gravt. The ceter of gravt G s a pot whch locates the resultat
More informationCredibility Premium Calculation in Motor Third-Party Liability Insurance
Advaces Mathematcal ad Computatoal Methods Credblty remum Calculato Motor Thrd-arty Lablty Isurace BOHA LIA, JAA KUBAOVÁ epartmet of Mathematcs ad Quattatve Methods Uversty of ardubce Studetská 95, 53
More informationSecurity Analysis of RAPP: An RFID Authentication Protocol based on Permutation
Securty Aalyss of RAPP: A RFID Authetcato Protocol based o Permutato Wag Shao-hu,,, Ha Zhje,, Lu Sujua,, Che Da-we, {College of Computer, Najg Uversty of Posts ad Telecommucatos, Najg 004, Cha Jagsu Hgh
More information10.5 Future Value and Present Value of a General Annuity Due
Chapter 10 Autes 371 5. Thomas leases a car worth $4,000 at.99% compouded mothly. He agrees to make 36 lease paymets of $330 each at the begg of every moth. What s the buyout prce (resdual value of the
More informationModels for Selecting an ERP System with Intuitionistic Trapezoidal Fuzzy Information
JOURNAL OF SOFWARE, VOL 5, NO 3, MARCH 00 75 Models for Selectg a ERP System wth Itutostc rapezodal Fuzzy Iformato Guwu We, Ru L Departmet of Ecoomcs ad Maagemet, Chogqg Uversty of Arts ad Sceces, Yogchua,
More informationFinite Production Rate Model With Quality Assurance, Multi-customer and Discontinuous Deliveries
Fte Producto Rate Model Wth ualty Assurace, Mult-custoer ad Dscotuous Delveres Yua-Shy Peter Chu, L-We L, Fa-Yu Pa 3, Sga Wag Chu * Departet of Idustral Egeerg Chaoyag Uversty of Techology, Tachug 43,
More informationT = 1/freq, T = 2/freq, T = i/freq, T = n (number of cash flows = freq n) are :
Bullets bods Let s descrbe frst a fxed rate bod wthout amortzg a more geeral way : Let s ote : C the aual fxed rate t s a percetage N the otoal freq ( 2 4 ) the umber of coupo per year R the redempto of
More informationRegression Analysis. 1. Introduction
. Itroducto Regresso aalyss s a statstcal methodology that utlzes the relato betwee two or more quattatve varables so that oe varable ca be predcted from the other, or others. Ths methodology s wdely used
More informationFuzzy Task Assignment Model of Web Services Supplier in Collaborative Development Environment
, pp.199-210 http://dx.do.org/10.14257/uesst.2015.8.6.19 Fuzzy Task Assget Model of Web Servces Suppler Collaboratve Developet Evroet Su Ja 1,2, Peg Xu-ya 1, *, Xu Yg 1,3, Wag Pe-e 2 ad Ma Na- 4,2 1. College
More informationRUSSIAN ROULETTE AND PARTICLE SPLITTING
RUSSAN ROULETTE AND PARTCLE SPLTTNG M. Ragheb 3/7/203 NTRODUCTON To stuatos are ecoutered partcle trasport smulatos:. a multplyg medum, a partcle such as a eutro a cosmc ray partcle or a photo may geerate
More informationChapter Eight. f : R R
Chapter Eght f : R R 8. Itroducto We shall ow tur our atteto to the very mportat specal case of fuctos that are real, or scalar, valued. These are sometmes called scalar felds. I the very, but mportat,
More informationCapacitated Production Planning and Inventory Control when Demand is Unpredictable for Most Items: The No B/C Strategy
SCHOOL OF OPERATIONS RESEARCH AND INDUSTRIAL ENGINEERING COLLEGE OF ENGINEERING CORNELL UNIVERSITY ITHACA, NY 4853-380 TECHNICAL REPORT Jue 200 Capactated Producto Plag ad Ivetory Cotrol whe Demad s Upredctable
More informationA Comparative Study for Email Classification
A Coparatve Study for Eal Classfcato Seogwook You ad Des McLeod Uversty of Souther Calfora, Los Ageles, CA 90089 USA Abstract - Eal has becoe oe of the fastest ad ost ecoocal fors of coucato. However,
More informationDynamic Two-phase Truncated Rayleigh Model for Release Date Prediction of Software
J. Software Egeerg & Applcatos 3 63-69 do:.436/jsea..367 Publshed Ole Jue (http://www.scrp.org/joural/jsea) Dyamc Two-phase Trucated Raylegh Model for Release Date Predcto of Software Lafe Qa Qgchua Yao
More informationSpeeding up k-means Clustering by Bootstrap Averaging
Speedg up -meas Clusterg by Bootstrap Averagg Ia Davdso ad Ashw Satyaarayaa Computer Scece Dept, SUNY Albay, NY, USA,. {davdso, ashw}@cs.albay.edu Abstract K-meas clusterg s oe of the most popular clusterg
More informationAutomated Event Registration System in Corporation
teratoal Joural of Advaces Computer Scece ad Techology JACST), Vol., No., Pages : 0-0 0) Specal ssue of CACST 0 - Held durg 09-0 May, 0 Malaysa Automated Evet Regstrato System Corporato Zafer Al-Makhadmee
More informationStatistical Pattern Recognition (CE-725) Department of Computer Engineering Sharif University of Technology
I The Name of God, The Compassoate, The ercful Name: Problems' eys Studet ID#:. Statstcal Patter Recogto (CE-725) Departmet of Computer Egeerg Sharf Uversty of Techology Fal Exam Soluto - Sprg 202 (50
More informationIntegrating Production Scheduling and Maintenance: Practical Implications
Proceedgs of the 2012 Iteratoal Coferece o Idustral Egeerg ad Operatos Maagemet Istabul, Turkey, uly 3 6, 2012 Itegratg Producto Schedulg ad Mateace: Practcal Implcatos Lath A. Hadd ad Umar M. Al-Turk
More informationSequences and Series
Secto 9. Sequeces d Seres You c thk of sequece s fucto whose dom s the set of postve tegers. f ( ), f (), f (),... f ( ),... Defto of Sequece A fte sequece s fucto whose dom s the set of postve tegers.
More informationECONOMIC CHOICE OF OPTIMUM FEEDER CABLE CONSIDERING RISK ANALYSIS. University of Brasilia (UnB) and The Brazilian Regulatory Agency (ANEEL), Brazil
ECONOMIC CHOICE OF OPTIMUM FEEDER CABE CONSIDERING RISK ANAYSIS I Camargo, F Fgueredo, M De Olvera Uversty of Brasla (UB) ad The Brazla Regulatory Agecy (ANEE), Brazl The choce of the approprate cable
More informationThe Time Value of Money
The Tme Value of Moey 1 Iversemet Optos Year: 1624 Property Traded: Mahatta Islad Prce : $24.00, FV of $24 @ 6%: FV = $24 (1+0.06) 388 = $158.08 bllo Opto 1 0 1 2 3 4 5 t ($519.37) 0 0 0 0 $1,000 Opto
More informationCHAPTER 2. Time Value of Money 6-1
CHAPTER 2 Tme Value of Moey 6- Tme Value of Moey (TVM) Tme Les Future value & Preset value Rates of retur Autes & Perpetutes Ueve cash Flow Streams Amortzato 6-2 Tme les 0 2 3 % CF 0 CF CF 2 CF 3 Show
More informationProject 3 Weight analysis
The Faculty of Power ad Aeroautcal Egeerg Arcraft Desg Departet Project 3 Weght aalyss Ths project cossts of two parts. Frst part cludes fuselage teror (cockpt) coceptual desg. Secod part cludes etoed
More informationMaintenance Scheduling of Distribution System with Optimal Economy and Reliability
Egeerg, 203, 5, 4-8 http://dx.do.org/0.4236/eg.203.59b003 Publshed Ole September 203 (http://www.scrp.org/joural/eg) Mateace Schedulg of Dstrbuto System wth Optmal Ecoomy ad Relablty Syua Hog, Hafeg L,
More informationWe present a new approach to pricing American-style derivatives that is applicable to any Markovian setting
MANAGEMENT SCIENCE Vol. 52, No., Jauary 26, pp. 95 ss 25-99 ess 526-55 6 52 95 forms do.287/msc.5.447 26 INFORMS Prcg Amerca-Style Dervatves wth Europea Call Optos Scott B. Laprse BAE Systems, Advaced
More informationn. We know that the sum of squares of p independent standard normal variables has a chi square distribution with p degrees of freedom.
UMEÅ UNIVERSITET Matematsk-statstska sttutoe Multvarat dataaalys för tekologer MSTB0 PA TENTAMEN 004-0-9 LÖSNINGSFÖRSLAG TILL TENTAMEN I MATEMATISK STATISTIK Multvarat dataaalys för tekologer B, 5 poäg.
More informationConversion of Non-Linear Strength Envelopes into Generalized Hoek-Brown Envelopes
Covero of No-Lear Stregth Evelope to Geeralzed Hoek-Brow Evelope Itroducto The power curve crtero commoly ued lmt-equlbrum lope tablty aaly to defe a o-lear tregth evelope (relatohp betwee hear tre, τ,
More informationA New Bayesian Network Method for Computing Bottom Event's Structural Importance Degree using Jointree
, pp.277-288 http://dx.do.org/10.14257/juesst.2015.8.1.25 A New Bayesa Network Method for Computg Bottom Evet's Structural Importace Degree usg Jotree Wag Yao ad Su Q School of Aeroautcs, Northwester Polytechcal
More informationThe simple linear Regression Model
The smple lear Regresso Model Correlato coeffcet s o-parametrc ad just dcates that two varables are assocated wth oe aother, but t does ot gve a deas of the kd of relatoshp. Regresso models help vestgatg
More informationThe Digital Signature Scheme MQQ-SIG
The Dgtal Sgature Scheme MQQ-SIG Itellectual Property Statemet ad Techcal Descrpto Frst publshed: 10 October 2010, Last update: 20 December 2010 Dalo Glgorosk 1 ad Rue Stesmo Ødegård 2 ad Rue Erled Jese
More informationReport 52 Fixed Maturity EUR Industrial Bond Funds
Rep52, Computed & Prted: 17/06/2015 11:53 Report 52 Fxed Maturty EUR Idustral Bod Fuds From Dec 2008 to Dec 2014 31/12/2008 31 December 1999 31/12/2014 Bechmark Noe Defto of the frm ad geeral formato:
More informationEfficient Traceback of DoS Attacks using Small Worlds in MANET
Effcet Traceback of DoS Attacks usg Small Worlds MANET Yog Km, Vshal Sakhla, Ahmed Helmy Departmet. of Electrcal Egeerg, Uversty of Souther Calfora, U.S.A {yogkm, sakhla, helmy}@ceg.usc.edu Abstract Moble
More informationOn formula to compute primes and the n th prime
Joural's Ttle, Vol., 00, o., - O formula to compute prmes ad the th prme Issam Kaddoura Lebaese Iteratoal Uversty Faculty of Arts ad ceces, Lebao Emal: ssam.addoura@lu.edu.lb amh Abdul-Nab Lebaese Iteratoal
More informationCommon p-belief: The General Case
GAMES AND ECONOMIC BEHAVIOR 8, 738 997 ARTICLE NO. GA97053 Commo p-belef: The Geeral Case Atsush Kaj* ad Stephe Morrs Departmet of Ecoomcs, Uersty of Pesylaa Receved February, 995 We develop belef operators
More informationSettlement Prediction by Spatial-temporal Random Process
Safety, Relablty ad Rs of Structures, Ifrastructures ad Egeerg Systems Furuta, Fragopol & Shozua (eds Taylor & Fracs Group, Lodo, ISBN 978---77- Settlemet Predcto by Spatal-temporal Radom Process P. Rugbaapha
More informationCurve Fitting and Solution of Equation
UNIT V Curve Fttg ad Soluto of Equato 5. CURVE FITTING I ma braches of appled mathematcs ad egeerg sceces we come across epermets ad problems, whch volve two varables. For eample, t s kow that the speed
More informationFundamentals of Mass Transfer
Chapter Fudametals of Mass Trasfer Whe a sgle phase system cotas two or more speces whose cocetratos are ot uform, mass s trasferred to mmze the cocetrato dffereces wth the system. I a mult-phase system
More informationMeasuring the Quality of Credit Scoring Models
Measur the Qualty of Credt cor Models Mart Řezáč Dept. of Matheatcs ad tatstcs, Faculty of cece, Masaryk Uversty CCC XI, Edurh Auust 009 Cotet. Itroducto 3. Good/ad clet defto 4 3. Measur the qualty 6
More informationHow do bookmakers (or FdJ 1 ) ALWAYS manage to win?
How do bookakers (or FdJ ALWAYS aage to w? Itroducto otatos & varables Bookaker's beeft eected value 4 4 Bookaker's strateges5 4 The hoest bookaker 6 4 "real lfe" bookaker 6 4 La FdJ 8 5 How ca we estate
More informationThree Dimensional Interpolation of Video Signals
Three Dmesoal Iterpolato of Vdeo Sgals Elham Shahfard March 0 th 006 Outle A Bref reve of prevous tals Dgtal Iterpolato Bascs Upsamplg D Flter Desg Issues Ifte Impulse Respose Fte Impulse Respose Desged
More informationDECISION MAKING WITH THE OWA OPERATOR IN SPORT MANAGEMENT
ESTYLF08, Cuecas Meras (Meres - Lagreo), 7-9 de Septembre de 2008 DECISION MAKING WITH THE OWA OPERATOR IN SPORT MANAGEMENT José M. Mergó Aa M. Gl-Lafuete Departmet of Busess Admstrato, Uversty of Barceloa
More informationPerformance Attribution. Methodology Overview
erformace Attrbuto Methodology Overvew Faba SUAREZ March 2004 erformace Attrbuto Methodology 1.1 Itroducto erformace Attrbuto s a set of techques that performace aalysts use to expla why a portfolo's performace
More informationPolyphase Filters. Section 12.4 Porat 1/39
Polyphase Flters Secto.4 Porat /39 .4 Polyphase Flters Polyphase s a way of dog saplg-rate coverso that leads to very effcet pleetatos. But ore tha that, t leads to very geeral vewpots that are useful
More informationANALYTICAL MODEL FOR TCP FILE TRANSFERS OVER UMTS. Janne Peisa Ericsson Research 02420 Jorvas, Finland. Michael Meyer Ericsson Research, Germany
ANALYTICAL MODEL FOR TCP FILE TRANSFERS OVER UMTS Jae Pesa Erco Research 4 Jorvas, Flad Mchael Meyer Erco Research, Germay Abstract Ths paper proposes a farly complex model to aalyze the performace of
More informationConstrained Cubic Spline Interpolation for Chemical Engineering Applications
Costraed Cubc Sple Iterpolato or Chemcal Egeerg Applcatos b CJC Kruger Summar Cubc sple terpolato s a useul techque to terpolate betwee kow data pots due to ts stable ad smooth characterstcs. Uortuatel
More information10/19/2011. Financial Mathematics. Lecture 24 Annuities. Ana NoraEvans 403 Kerchof AnaNEvans@virginia.edu http://people.virginia.
Math 40 Lecture 24 Autes Facal Mathematcs How ready do you feel for the quz o Frday: A) Brg t o B) I wll be by Frday C) I eed aother week D) I eed aother moth Aa NoraEvas 403 Kerchof AaNEvas@vrga.edu http://people.vrga.edu/~as5k/
More informationStatistical Techniques for Sampling and Monitoring Natural Resources
Uted States Departmet of Agrculture Forest Servce Statstcal Techques for Samplg ad Motorg Natural Resources Rocky Mouta Research Stato Geeral Techcal Report RMRS-GTR-6 Has T. Schreuder, Rchard Erst, ad
More informationAnalysis of Multi-product Break-even with Uncertain Information*
Aalyss o Mult-product Break-eve wth Ucerta Iormato* Lazzar Lusa L. - Morñgo María Slva Facultad de Cecas Ecoómcas Uversdad de Bueos Ares 222 Córdoba Ave. 2 d loor C20AAQ Bueos Ares - Argeta lazzar@eco.uba.ar
More informationISyE 512 Chapter 7. Control Charts for Attributes. Instructor: Prof. Kaibo Liu. Department of Industrial and Systems Engineering UW-Madison
ISyE 512 Chapter 7 Cotrol Charts for Attrbutes Istructor: Prof. Kabo Lu Departmet of Idustral ad Systems Egeerg UW-Madso Emal: klu8@wsc.edu Offce: Room 3017 (Mechacal Egeerg Buldg) 1 Lst of Topcs Chapter
More informationIncorporating demand shifters in the Almost Ideal demand system
Ecoomcs Letters 70 (2001) 73 78 www.elsever.com/ locate/ ecobase Icorporatg demad shfters the Almost Ideal demad system Jula M. Alsto, James A. Chalfat *, Ncholas E. Pggott a,1 1 a, b a Departmet of Agrcultural
More informationLoad Balancing via Random Local Search in Closed and Open systems
Load Balacg va Rado Local Search Closed ad Ope systes A. Gaesh Dept. of Matheatcs Uversty of Brstol, UK a.gaesh@brstol.ac.u A. Proutere Mcrosoft Research Cabrdge, UK aproute@crosoft.co S. Llethal Stats
More informationOptimal replacement and overhaul decisions with imperfect maintenance and warranty contracts
Optmal replacemet ad overhaul decsos wth mperfect mateace ad warraty cotracts R. Pascual Departmet of Mechacal Egeerg, Uversdad de Chle, Caslla 2777, Satago, Chle Phoe: +56-2-6784591 Fax:+56-2-689657 rpascual@g.uchle.cl
More informationRQM: A new rate-based active queue management algorithm
: A ew rate-based actve queue maagemet algorthm Jeff Edmods, Suprakash Datta, Patrck Dymod, Kashf Al Computer Scece ad Egeerg Departmet, York Uversty, Toroto, Caada Abstract I ths paper, we propose a ew
More informationMobile Agents in Telecommunications Networks A Simulative Approach to Load Balancing
Moble Agets Telecommucatos Networks A Smulatve Approach to Load Balacg Steffe Lpperts Departmet of Computer Scece (4), Uversty of Techology Aache Aache, 52056, Germay Ad Brgt Kreller Corporate Techology
More informationSTATISTICS IN TRANSITION new series
STATISTICS IN TRANSITION ew seres A Iteratoal Joural of the Polsh Statstcal Assocato CONTENTS Edtor s ote ad acowledgets... Subsso forato for authors... Saplg ad estato ethods BAGNATO L. PUNZO A. Noparaetrc
More informationAn Approach to Evaluating the Computer Network Security with Hesitant Fuzzy Information
A Approach to Evaluatg the Computer Network Securty wth Hestat Fuzzy Iformato Jafeg Dog A Approach to Evaluatg the Computer Network Securty wth Hestat Fuzzy Iformato Jafeg Dog, Frst ad Correspodg Author
More informationA Single-Producer Multi-Retailer Integrated Inventory System with Scrap in Production
Research Joural of Appled Sceces, Egeerg ad Techology 5(4): 54-59, 03 ISSN: 040-7459; e-issn: 040-7467 Maxwell Scetfc Orgazato, 03 Subtted: July 09, 0 Accepted: August 08, 0 Publshed: February 0, 03 A
More informationSTOCHASTIC approximation algorithms have several
IEEE TRANSACTIONS ON INFORMATION THEORY, VOL 60, NO 10, OCTOBER 2014 6609 Trackg a Markov-Modulated Statoary Degree Dstrbuto of a Dyamc Radom Graph Mazyar Hamd, Vkram Krshamurthy, Fellow, IEEE, ad George
More informationMathematics of Finance
CATE Mathematcs of ace.. TODUCTO ths chapter we wll dscuss mathematcal methods ad formulae whch are helpful busess ad persoal face. Oe of the fudametal cocepts the mathematcs of face s the tme value of
More informationNetwork dimensioning for elastic traffic based on flow-level QoS
Network dmesog for elastc traffc based o flow-level QoS 1(10) Network dmesog for elastc traffc based o flow-level QoS Pas Lassla ad Jorma Vrtamo Networkg Laboratory Helsk Uversty of Techology Itroducto
More informationAn Evaluation of Naïve Bayesian Anti-Spam Filtering Techniques
Proceedgs of the 2007 IEEE Workshop o Iformato Assurace Uted tates Mltary Academy, West Pot, Y 20-22 Jue 2007 A Evaluato of aïve Bayesa At-pam Flterg Techques Vkas P. Deshpade, Robert F. Erbacher, ad Chrs
More informationUSEFULNESS OF BOOTSTRAPPING IN PORTFOLIO MANAGEMENT
USEFULNESS OF BOOTSTRAPPING IN PORTFOLIO MANAGEMENT Radovaov Bors Faculty of Ecoomcs Subotca Segedsk put 9-11 Subotca 24000 E-mal: radovaovb@ef.us.ac.rs Marckć Aleksadra Faculty of Ecoomcs Subotca Segedsk
More informationLecture 7. Norms and Condition Numbers
Lecture 7 Norms ad Codto Numbers To dscuss the errors umerca probems vovg vectors, t s usefu to empo orms. Vector Norm O a vector space V, a orm s a fucto from V to the set of o-egatve reas that obes three
More informationReinsurance and the distribution of term insurance claims
Resurace ad the dstrbuto of term surace clams By Rchard Bruyel FIAA, FNZSA Preseted to the NZ Socety of Actuares Coferece Queestow - November 006 1 1 Itroducto Ths paper vestgates the effect of resurace
More informationα 2 α 1 β 1 ANTISYMMETRIC WAVEFUNCTIONS: SLATER DETERMINANTS (08/24/14)
ANTISYMMETRI WAVEFUNTIONS: SLATER DETERMINANTS (08/4/4) Wavefuctos that descrbe more tha oe electro must have two characterstc propertes. Frst, scll electros are detcal partcles, the electros coordates
More informationDe-Duplication Scheduling Strategy in Real-Time Data Warehouse
Sed Orders for Reprts to reprts@bethascece.ae he Ope Cyberetcs & Systecs Joural, 25, 9, 37-43 37 Ope Access De-Duplcato Schedulg Strategy Real-e Data Warehouse Hu Lu, Je Sog 2,*, JBoWu 2, ad Yu-B Bao 3
More informationOn Error Detection with Block Codes
BULGARIAN ACADEMY OF SCIENCES CYBERNETICS AND INFORMATION TECHNOLOGIES Volume 9, No 3 Sofa 2009 O Error Detecto wth Block Codes Rostza Doduekova Chalmers Uversty of Techology ad the Uversty of Gotheburg,
More informationA Parallel Transmission Remote Backup System
2012 2d Iteratoal Coferece o Idustral Techology ad Maagemet (ICITM 2012) IPCSIT vol 49 (2012) (2012) IACSIT Press, Sgapore DOI: 107763/IPCSIT2012V495 2 A Parallel Trasmsso Remote Backup System Che Yu College
More informationProceedings of the 2010 Winter Simulation Conference B. Johansson, S. Jain, J. Montoya-Torres, J. Hugan, and E. Yücesan, eds.
Proceedgs of the 21 Wter Smulato Coferece B. Johasso, S. Ja, J. Motoya-Torres, J. Huga, ad E. Yücesa, eds. EMPIRICAL METHODS OR TWO-ECHELON INVENTORY MANAGEMENT WITH SERVICE LEVEL CONSTRAINTS BASED ON
More informationModeling of Router-based Request Redirection for Content Distribution Network
Iteratoal Joural of Computer Applcatos (0975 8887) Modelg of Router-based Request Redrecto for Cotet Dstrbuto Network Erw Harahap, Jaaka Wjekoo, Rajtha Teekoo, Fumto Yamaguch, Shch Ishda, Hroak Nsh Hroak
More informationEMERGING MARKETS: STOCK MARKET INVESTING WITH POLITICAL RISK. Ephraim Clark and Radu Tunaru
EMERGING MARKETS: STOCK MARKET INVESTING WITH POLITICAL RISK By Ephram Clark ad Radu Tuaru Correspodace to: Ephram Clark Mddlesex Uversty Busess School The Burroughs Lodo NW4 4BT UK Tel: 44-(0)08-36-530
More informationA Bayesian Networks in Intrusion Detection Systems
Joural of Computer Scece 3 (5: 59-65, 007 ISSN 549-3636 007 Scece Publcatos A Bayesa Networs Itruso Detecto Systems M. Mehd, S. Zar, A. Aou ad M. Besebt Electrocs Departmet, Uversty of Blda, Algera Abstract:
More informationBanking (Early Repayment of Housing Loans) Order, 5762 2002 1
akg (Early Repaymet of Housg Loas) Order, 5762 2002 y vrtue of the power vested me uder Secto 3 of the akg Ordace 94 (hereafter, the Ordace ), followg cosultato wth the Commttee, ad wth the approval of
More informationOptimal Packetization Interval for VoIP Applications Over IEEE 802.16 Networks
Optmal Packetzato Iterval for VoIP Applcatos Over IEEE 802.16 Networks Sheha Perera Harsha Srsea Krzysztof Pawlkowsk Departmet of Electrcal & Computer Egeerg Uversty of Caterbury New Zealad sheha@elec.caterbury.ac.z
More information