MR(2000) ½ 62N01 / Î O213 A Ê (2012)
|
|
- Barnard Hubbard
- 7 years ago
- Views:
Transcription
1 Á41ÁÁ6 Vol.41, No ½ ADVANCES IN MATHEMATICS Dec., 2012 º È ² Âͺ ÑÜÖº ÄÅ «² 1,2,, «Ý 1, Đ 3 (1. ÉÐ «Ì È«É Æ ; 2. Ç «¼ «Ì «¼ Ç ; 3. È ««Ð ) 0 Ã É Ø Ù± ß Õ Ö ÜÛ ³ Ò Õ ÑÆÅ Ú EM Û Ð Ñ ³ Ð Ô ÞÛ Ú ³ ÕÓ Û Ø ³ Ò Õ EM MR(2000) ½ 62N01 / Î O213 A Ê (2012) Gupta Kundu(1999) [1] Ľ ß Á ÅÁ Gamma Weibull Î Â Æ Æ ÁÔ ± Þ Ë Æ ß Á ± Ú ÉÆ Ô¹È²Ë ÅÎ ß µý Ú Üµ «Ñß Á à ² [2 8]. Ú Æ È ² ½Ö ³¾ Æ [9 11]. EM ÎÅ Ê Ñ ß Á Ù ß Á Û ÕÌ Ô ½ f(x;α,λ) = αλ(1 e λx ) α 1 e λx, x 0, (1) S(x;α,λ) = 1 (1 e λx ) α, x 0, (2) h(x;α,λ) = f(x;α,λ) S(x;α,λ) = αλ(1 e λx ) α 1 e λx 1 (1 e λx ) α, x 0, (3) ÅÈ α,λ > 0 ¼Û»Ì α = 1 Û «Á Û Û (1) Ô h(x;α,λ) ϵ λ, ϵ α. α > 1 h(x;α,λ) ½Â α < 1 h(x;α,λ) ½Â³ α = 1 h(x;α,λ) ½² [4]. À 1 ² Ù À 2 EM Å Û Ù À 3 ÀÛ À 4 ¾ ß Á Û Î Ûß»º È«ÌÄÛß (No ) ÉÐ «±È«Ûß (ÛßÙ Ò ÊÇ Ü Ì No. 12XNH161). pole1999@163.com
2 756 «41Á 1 Đ ¹ «Ç ± (1) Ûݹ»³ ¹ Þ± Ú ß Á (1), Å F(x;α,λ) = (1 e λx ) α, x 0. (4) Ö n ± Ú¾ Ñ [0,+ ) N +1 ± N ± [T i 1,T i ), ÅÈ i = 1,2,,N; 0 = T 0 < T 1 < < T N < +. c i ¼ [T i 1,T i ) È µý± d i ¼ T i ˾ ± ² n = N (c i +d i ). L(α,λ) = Î logl(α,λ) = = N [F(T i ;α,λ) F(T i 1 ;α,λ)] ci [1 F(T i ;α,λ)] di N [( 1 e λt i ) α ( 1 e λt i 1 ) α ] ci ( [ 1 1 e λt i ) α ] di. { ci log [( 1 e λti) α ( 1 e λt i 1 ) α ] +di log [ 1 ( 1 e λti) α]}. Î Î logl(α,λ) α = = 0, { (1 e λti ) α log(1 e λti ) (1 e λti 1 ) α log(1 e λti 1 ) c i (1 e λti ) α (1 e λti 1 ) α d i (1 e λti ) α log(1 e λti ) (1 e λti ) α } logl(α,λ) λ = α = 0. { (1 e λti ) α 1 e λti T i (1 e λti 1 ) α 1 e λti 1 T i 1 c i (1 e λti ) α (1 e λti 1 ) α d i (1 e λti ) α 1 e λti T i 1 (1 e λti ) α } ¹ É α,λ Ù ½±µ Ù ¹ Ù Ó» ¹¾ À ( Ï ) Ù ½Ú ÑÖ EM Ó Ý Ù 2 Õ¹ Ðß 2.1 EM ¼Þ Dempster µ 1977 Ľ EM ½ Ê Î ² µ (missing data) Û MLE Æ ÁÏ Þ (observed data) Î MLE. Ç
3 6 ȹ ÈÒ Ò Â Ú 757 Z = (Y,X) ½±Þ Y µ X f(y,x η) ½ Z Õ Ì f(x Y,η) ½ÑÇÞ Y = y ÉµÑ µ X ɵÕÌ ÅÈ η ½ Ù η MLE ½ÊĐ Þ Y Î L(η Y) À Å L(η Y), Šѽ Î L(η Z) = log[f(y η) f(x Y,η)]. EM Í Í E M E ÑǼÀ η (0), À t 1 Æ η Ù η (t 1), Ç Î À Q Q(η η (t 1) ) = L(η Z) f(x Y,η)dX = E η (t 1){L(η Z)}. η (t 1) M Å Q(η η (t 1) ) η Ó η (t). ÍË E M ¹ Ù ÀÎ η (t) η (t 1) ÜµÞ ÜÀ ε Ã É Ø Å L(η Y) Ú µ Å Q È Ë η (0) ¼ à 2.2 Ó ÆÒÏ Þ n ± Ú X 1,X 2,,X n Ë Ë µ ß Á (1), Î n ± Ú¾ ÁÔ ± [T i 1,T i ) T i Ë ¾ ÔÄĐÞ ± Ú ± [T i 1,T i ) È X j c i T i Ë ¾ X j d i, ÅÈ i = 1,2,,N; j = 1,2,,n; 0 = T 0 < T 1 < < T N < +. ± Ú Å X = (X 1,X 2,,X n ), ½ X ½ ÉÞ EM ȵ µ ĐÞ Y = (c 1,c 2,,c N,d 1,d 2,, d N ), ÁÔ «Ø Z = (X,Y). EM Ô X ih,x il, ÁÔ ¼ ± [T i 1,T i ) T i Ë ¾ ± Ú ÑÖ ÔÒ EM È E M Î Ù Ù ±µ X Þ Y À² µ½ Ô² f(α,λ X,Y) = f(α,λ X). ± ß Á (1) ÕÌ Î ½ logf(α,λ X) = log = n log(αλ)+ N [{ ( ) αλ 1 e λx ih α 1e } λx ci ( ) ih { αλ 1 e λx il α 1e } λx di ] il { ci log [( 1 e λx ) ih α 1e ] λx ih +di log [( 1 e λx ) il α 1e ]} λx il. ÑÇ ¼À α (0),λ (0), EM Í E ÑÇ À t 1 Ù α (t 1),λ (t 1), À t Q Q(α,λ α (t 1),λ (t 1),Y) = E [ logf(α,λ X) α (t 1),λ (t 1),Y ] = n log(αλ)+ + c i E { log [( 1 e λx ) ih α 1e ] λx ih α (t 1),λ (t 1),Y } d i E { log [( 1 e λx il) α 1e ] λx il α (t 1),λ (t 1),Y }.
4 758 «41Á Q È X ih X il ɵ ÕÌ p ih (x) = f ih (x α (t 1),λ (t 1),Y) = α(t 1) λ (t 1) (1 e λ(t 1)x ) α(t 1) 1 e λ(t 1) x (1 e λ(t 1) T i) α (t 1) (1 e λ(t 1) T i 1) α (t 1), x [T i 1,T i ) µ½ p il (x) = f il (x α (t 1),λ (t 1),Y) = α(t 1) λ (t 1) (1 e λ(t 1)x ) α(t 1) 1 e λ(t 1) x, x [T 1 (1 e λ(t 1) T i) α (t 1) i,+ ). Q(α,λ α (t 1),λ (t 1),Y) Ti = n log(αλ)+ c i p ih (x) log[(1 e λx ) α 1 e λx ]dx T i d i p il (x) log[(1 e λx ) α 1 e λx ]dx. T i M Å Q α,λ À t Ù α (t),λ (t), Q(α,λ α (t 1),λ (t 1),Y) Î α,λ Q(α,λ α (t 1),λ (t 1),Y) Àà α (t),λ (t). Î α,λ Q α = n N α + Ti c i T i 1 p ih (x) log(1 e λx )dx+ + d i p il (x) log(1 e λx )dx, Q λ = n N λ + Ti c i p ih (x) x(αe λx 1) + T i 1 1 e λx dx+ d i p il (x) x(αe λx 1) T i 1 e λx dx. Q α = 0, Q λ = 0, É α = n Ti c i T i 1 p ih (x) log(1 e λx )dx+ N T i, (5) + d i T i p il (x) log(1 e λx )dx n λ =. (6) Ti c i T i 1 p ih (x) x(αe λx 1) 1 e dx+ N + d λx i T i p il (x) x(αe λx 1) 1 e dx λx Ö ½ (5), (6) ½À (α (t),λ (t) ), Æ (α (t 1),λ (t 1) ) (α (t),λ (t) ), Ë Ö (5), (6)» Å α,λ à 3 X i, i = 1,2,,n ½Î ß Á Û (1) Ë Ë ÔÅ [8] ȹ Û Ç α = 1.50, λ = 0.06, N = 9 10 T 0 = 0, T 1 = 5.5, T 2 = 10.5, T 3 = 15.5, T 4 = 20.5, T 5 = 25.5, T 6 = 30.5, T 7 = 40.5, T 8 = 50.5, T 9 =
5 6 ȹ ÈÒ Ò Â Ú , T 10 = +, Ì 0.001, Î j 8, ± T j ¾ j 9, T 9 À² µý ± Ê ¾ Å n = 60, 120, 200, 500, 1000 ÐË ¾ s = 100, 200, 500 Ù Ý À k ¾ Ù η k = (α k,λ k )(k = 1,2,,s), Ù À Ù Â mean j = 1 s s k=1 η k j, mse j = 1 s 1 s ( ) η k 2, j mean j ÅÈ η j ¼ η À j Ù Ú 1 2. À² ± Matlab2009b µ Ö 1 2 É Ä EM ε ³¾ Ñß Á ² Ù Ý Û Ë ÅÙ Ý Ó 1 ÅÆ ÁÌ ÐÚÔ Ë (mean) k=1 η = (α,λ) n s ˆα ˆλ E E E E E E 2 (1.5, 0.06) E E E E E E E E E 2 2 ÅÆ ÁÌ ÐÚÔ (mse) η = (α,λ) n s ˆα ˆλ E E E E E E E E E E E E 5 (1.5, 0.06) E E E E E E E E E E E E E E E E E E 6
6 760 «41Á 4 À ¹ Đ ÎØ Ð¹Í½Ý ÉÐÕ Ð À À «¾ µð Ñ 2418 Ð¹Í Ð [12] È Parker(1946) Ô ±½ Í ±«² 16 ± 15 ±³Ì I j = (j 1,j], j = 1,2,,15, I 16 = (15, ). Ó ±È µ 3 À¼ 3 ¾ ÚµÙ Interval Death numbers Outfollowed numbers I j D j W j [12] Ƚ ØÙ Ù Ô Í Ï À Ý À 10 ¼ º ± É Ô 10 «¼ Å Ê ÆĐ Í½» ÆÌ 5 ½ Å ß Á Û (1) EM α»ì λ Ù ˆα = 0.769, ˆλ = 0.106, Ô ½ Ŝ(x) = 1 (1 e 0.769x ) 0.106, x 0, (7) ĥ(x) = (1 e 0.769x ) e 0.769x 1 (1 e 0.769x ) 0.106, x 0. (8) ±µ Ù ˆα = < 1, Û Ô ½Â³ Ô 1. 1 Ä Ô ½ ų 2 Úμ À , À , À 3 ú À 10 ³¼Ñ À 10 ú À 30 ³ ²«Ñ º ³ Ò ÚÛ (7) (8),  ڽ ( ), 5 ½ ( [12] È ¼½ ). Ë ÚÁ ½ ³ Ú Ë t ³
7 6 ȹ ÈÒ Ò Â Ú 761 ÚÖ» µ(t) = 1 S(t) t S(x)dx Survival function Survival value years diagnosed 0.18 Hazard function 0.16 Hazard value years diagnosed 1 ĐºÎ ² Õ ± 1 ³ Ú½ ( ), 5 ³ Ú½ ( ), 10 ³ Ú½ ( ). ± Ë É ½ Å Ê ÆĐ Í½ ³ Ú ³Þ Ö Å ÍÄ Ç Ð¹Í Ý Î Ð¹Í Æ Â³ Ú Ä Õ [1] Gupta, R.D. and Kundu, D., Generalized exponential distributions, Austr. New Zealand J. Statist., 1999, 41(2): [2] Raqab, M.Z., Inferences for generalized exponential distribution based on record statistics, J. Statist. Plann. Inference, 2002, 104(2): [3] Sarhan, A.M., Analysis of incomplete, censored data in competing risks models with generalized exponential distribution, IEEE Trans. Reliability, 2007, 56(1): [4] Gupta, R.D. and Kundu, D., Generalized exponential distribution: existing results and some recent developments, J. Statist. Plann. Inference., 2007, 137(11): [5] Raqab, M.Z. and Madi, M.T., Bayesian inference for the generalized exponential distribution, J. Statist. Comput. Simul., 2005, 75(10): [6] Gupta, R.D. and Kundu, D., Generalized exponential distribution: Bayesian estimations, Comput. Statist. Data Anal., 2008, 52(4): [7] Kundu, D. and Pradhan, B., Estimating the parameters of the generalized exponential distribution in presence of hybrid censoring, Communications in Statistics Theory and Methods, 2009, 38(12):
8 762 «41Á [8] Chen D.G. and Lio, Y.L., Parameter estimations for generalized exponential distribution under progressive type-i interval censoring, 2010, 54(6): [9] Pettitt, A.N., Re-weighted least squares estimation with censored and grouped data: an application of the EM algorithm, Royal Statistical Society, 1985, 47(2): [10] Liu L.P. Estimation of MLE for Weibull distribution with grouped and censored data, Chinese Journal of Applied Probability and Statistics, 2001, 17(2): [11] Liu X., Chen H. and Fei H.L., Estimation of the parameters in the lognormal distribution with grouped and right-censored data, Chinese Journal of Applied Probability and Statistics, 2008, 24(4): [12] Lee, E.T. and Wang J.W., Statistical Methods for Survival Data Analysis(3rd Edition), New York: John Wiley & Sons, Parameters Estimation and Application of Generalized Exponential Distribution Under Grouped and Right-censored Data TIAN Yuzhu 1,2, TIAN Maozai 1, CHEN Ping 3 (1. Center for Applied Statistics, Renmin University of China, Beijing, , P. R. China; 2. School of Mathematics and Statistics, Tianshui Normal University, Tianshui, Gansu, , P. R. China; 3. Dependment of Mathematics, Southeast University, Nanjing, Jiangsu, , P. R. China) Abstract: Generalized exponential distribution is a class of important distribution in lifedata analysis, especially in some skewed lifedata. The estimation problem for generalized exponential distribution model with grouped and right-censored data is considered. The maximum likelihood estimators by using the EM algorithm are obtained. Some simulations are carried out to illustrate that proposed algorithm is effective to the model. Finally, a set of medicine data is analyzed by use of generalized exponential distribution. Key words: generalized exponential distribution; grouped and right-censored data; EM algorithm
Professional Liability Errors and Omissions Insurance Application
If coverage is issued, it will be on a claims-made basis. Notice: this insurance coverage provides that the limit of liability available to pay judgements or settlements shall be reduced by amounts incurred
More informationØÓÖ Ò Ê Ø ÓÒ Ð ÈÓÐÝÒÓÑ Ð ÓÚ Ö Ø ÓÑÔÐ Ü ÆÙÑ Ö Ò Ö Ø ÂÓ Ò ÒÒÝ Ý Ì ÓÑ ÖÖ ØÝ Þ ÂÓ Ï ÖÖ Ò Ü ÖÙ ÖÝ ½ ØÖ Ø Æ Ð ÓÖ Ø Ñ Ö Ú Ò ÓÖ Ø ÖÑ Ò Ò Ø ÒÙÑ Ö Ò Ö Ó Ø ØÓÖ ÖÖ Ù Ð ÓÚ Ö Ø ÓÑÔÐ Ü ÒÙÑ Ö Ó ÑÙÐØ ¹ Ú Ö Ø ÔÓÐÝÒÓÑ Ð
More informationÒ ÒØ Ò ØÖ Ò Ô Ö ÒØ Ø Ö Ñ Ö Ø ÓÒ Ñ Ò Ø Èž ÖÙÒØ Ñ Ý Ø Ñ Ö ÒØÓÒ Ù ÄÙ ÓÙ Ò Ê ÝÑÓÒ Æ ÑÝ Ø ÄÁÈ ÆË ÄÝÓÒ ³ÁØ ÄÝÓÒ Ü ¼ Ö Ò º ÓÒØ Ø Ö º ÒØÓÒ Ù ÄÙº ÓÙ Ê ÝÑÓÒ ºÆ ÑÝ Ø Ò ¹ÝÓÒº Öº ØÖ Øº Ì Ô Ô Ö Ö Ò Û Ó¹ Ö ÔÔÖÓ ØÓ Ø
More informationű Ű ű ű ű űű ű ő ő ű ű ő ő ő Ű ű ő ő Ű ő ű ű ő ű ű Ű ű Ő ű ű Ő Ű ű ű Ű Ű ő ű Ű ű ű ű Ű Ű Ű ő ő ű ő ű Ű Ő ő ő Ő ő ű ő ő Ő ű Ű ű ő Ű Ő ű ő ő ű Ő Ű ű ő ő ő Ő Ű Ő ű ő ű ű Ű Ű ű Ű ű Ű ű Ű Ű ű ű ű Ő ŰŐ ő Ű ő
More informationFebruary 3, 2015. Scott Cline City College of San Francisco 50 Phelan Avenue San Francisco, CA
February 3, 2015 Scott Cline City College of San Francisco 50 Phelan Avenue San Francisco, CA RE: Fungal Investigation City College of San Francisco Administration Building 31 Gough Street San Francisco,
More informationÒ ÐÝÞ Ò ÔÐÓÊ ÓÛÒÐÓ ÈÖÓ Ð Û Ø ÁÒ¹ Ø ÐÐ ÒØ Å Ò Ö À Þ Ö ËÓ Ý Ò Ò Ü Ð Ï ÖÛ ØÞ ½ ½ ÁÒ Ø ØÙØ ĐÙÖ ËØ Ø Ø ÙÒ ĐÇ ÓÒÓÑ ØÖ ÀÙÑ ÓÐ Ø ÍÒ Ú Ö ØĐ Ø ÞÙ ÖÐ Ò ËÔ Ò Ù Ö ËØÖº ½ ½¼½ ÖÐ Ò ËÙÑÑ ÖÝ Ì Ô Ô Ö Ò Ü ÑÔÐ Ó Ø Ñ Ò Ò Ò
More informationService -realization. Imported web -service interfaces. Web -service usage interface. Web -service specification. client. build/buy reuse/buy
Ò Å Ø Ó ÓÐÓ Ý ÓÖ Ï Ë ÖÚ Ò Ù Ò ÈÖÓ Å ÈºÈ Ô ÞÓ ÐÓÙ Ò Â Ò Ò ÁÒ ÓÐ Ì Ð ÙÖ ÍÒ Ú Ö ØÝ ÈÇ ÓÜ ¼½ ¼¼¼ Ä Ì Ð ÙÖ Æ Ø ÖÐ Ò Ñ Ô Ò Ù ºÒÐ ØÖ Øº ¹ Ù Ò Ø Ò ØØ ÒØ ÓÒ ÖÓÑ ÓÑÔÓÒ ÒØ ØÓ Û ÖÚ ÔÔÐ Ø ÓÒ º ÅÓ Ø ÒØ ÖÔÖ Ô Ò ÑÓ Ø
More informationProceedings of the 5 th Annual Linux Showcase & Conference
USENIX Association Proceedings of the 5 th Annual Linux Showcase & Conference Oakland, California, USA November 5 10, 2001 THE ADVANCED COMPUTING SYSTEMS ASSOCIATION 2001 by The USENIX Association All
More informationORB User Sponsor Client Authenticate User Request Principal Create Credentials Authenticator Attributes ORB
Ö Ñ ÛÓÖ ÓÖ ÁÑÔÐ Ñ ÒØ Ò ÊÓÐ ¹ ÓÒØÖÓÐ Í Ò ÇÊ Ë ÙÖ ØÝ Ë ÖÚ ÃÓÒ Ø ÒØ Ò ÞÒÓ ÓÚ Ò Ò ÒØ Ö ÓÖ Ú Ò ØÖ ÙØ ËÝ Ø Ñ Ò Ò Ö Ò Ë ÓÓÐ Ó ÓÑÔÙØ Ö Ë Ò ÐÓÖ ÁÒØ ÖÒ Ø ÓÒ Ð ÍÒ Ú Ö ØÝ ØÖ Ø Ì Ô Ô Ö ÓÛ ÓÛ ÖÓÐ ¹ ÓÒØÖÓÐ Ê µ ÑÓ Ð ÓÙÐ
More informationÙ ØÓÑ Ö Ö ÔÓÒ Ð Ø À Ú Ð Ö À Ú Ø Ñ ØÓ Ù Ú ÁÒ Ø Ø Ñ Ø Ò Ä Ñ Ø ÔÖÓ Ø ÐÛ Ý Ú Ø Ñ ½¹½ Ì Ù ØÓÑ Ö ÓÙÐ ººº ß Ú Ð Ö ÙØ Ñ Ý ÒÓØ ÓÑÔÐ Ø µ Ó Û Ø» Û ÒØ º ß Ú Ø Ñ ØÓ Ù Ø Ö ÕÙ Ö Ñ ÒØ Û Ø Ø ÖÓÙÔ ÙÖ Ò Ø ÔÖÓ Øº ß Ð ØÓ Ú
More informationBayesian Estimation of Joint Survival Functions in Life Insurance
ISBA 2, Proceedings, pp. ISBA and Eurostat, 21 Bayesian Estimation of Joint Survival Functions in Life Insurance ARKADY SHEMYAKIN and HEEKYUNG YOUN University of St. Thomas, Saint Paul, MN, USA Abstract:
More information½ È Ø¹Ä Ú Ð ÌÖ Æ Å ÙÖ Ñ ÒØ ÖÓÑ Ì Ö¹½ ÁÈ ÓÒ Ù Ö Ð ËÙ ÅÓÓÒ ÖÝ Ò ÄÝÐ ÓØØÓÒ ÅÙ Ã Ò ÅÓÐÐ ÊÓ ÊÓ ÐÐ Ì Ë ÐÝ Ö ØÓÔ ÓØ ØÖ Ø Æ ØÛÓÖ ØÖ Æ Ñ ÙÖ Ñ ÒØ ÔÖÓÚ ÒØ Ð Ø ÓÖ Ò ØÛÓÖ Ò Ö Ö Ò Ò ØÛÓÖ Ñ Ò Ñ Òغ ÁÒ Ø Ô Ô Ö Û Ö Ô Ú
More informationModeling and Analysis of Call Center Arrival Data: A Bayesian Approach
Modeling and Analysis of Call Center Arrival Data: A Bayesian Approach Refik Soyer * Department of Management Science The George Washington University M. Murat Tarimcilar Department of Management Science
More informationReliability estimators for the components of series and parallel systems: The Weibull model
Reliability estimators for the components of series and parallel systems: The Weibull model Felipe L. Bhering 1, Carlos Alberto de Bragança Pereira 1, Adriano Polpo 2 1 Department of Statistics, University
More information200609 - ATV - Lifetime Data Analysis
Coordinating unit: Teaching unit: Academic year: Degree: ECTS credits: 2015 200 - FME - School of Mathematics and Statistics 715 - EIO - Department of Statistics and Operations Research 1004 - UB - (ENG)Universitat
More informationN servers. Load-Balancing. A(t) speed s. clients. αn servers. (i) speed s. N servers speed αs. (ii)
ËÀÊ ÆÃ Ò Ï Ë ÖÚ Ö ÖÑ Å Ø Ó ÓÖ Ë Ð Ð È Ö ÓÖÑ Ò ÈÖ Ø ÓÒ Ò Å ÙÖ Ñ ÒØ ÃÓÒ Ø ÒØ ÒÓ È ÓÙÒ Ô ÖØÑ ÒØ Ó Ð ØÖ Ð Ò Ò Ö Ò Ò ÓÑÔÙØ Ö Ë Ò ÍÒ Ú Ö ØÝ Ó ËÓÙØ ÖÒ Ð ÓÖÒ Ñ Ð Ô ÓÙÒ Ù º Ù Ô ÓÒ ¼¼½¹¾½ ¹ ¼ Ö ¼ Å Ð ÒØÓ Ú º ¼ ÄÓ
More informationQuery in mediated schema. Query Reformulation. Query in the union of exported source schemas. Query Optimization. Distributed query execution plan
ÔØ Ö ½ ÄÇ Á ¹ Ë Ì ÀÆÁÉÍ Ë ÁÆ Ì ÁÆÌ Ê ÌÁÇÆ ÐÓÒ º Ä ÚÝ Ô ÖØÑ ÒØ Ó ÓÑÔÙØ Ö Ë Ò Ò Ò Ò Ö Ò ÍÒ Ú Ö ØÝ Ó Ï Ò ØÓÒ Ë ØØÐ Ï ½ ÐÓÒ ºÛ Ò ØÓÒº Ù ØÖ Ø Ã ÝÛÓÖ Ì Ø ÒØ Ö Ø ÓÒ ÔÖÓ Ð Ñ ØÓ ÔÖÓÚ ÙÒ ÓÖÑ ØÓ ÑÙÐØ ÔÐ Ø ÖÓ Ò ÓÙ
More informationC o a t i a n P u b l i c D e b tm a n a g e m e n t a n d C h a l l e n g e s o f M a k e t D e v e l o p m e n t Z a g e bo 8 t h A p i l 2 0 1 1 h t t pdd w w wp i j fp h D p u b l i c2 d e b td S t
More informationGoodness of Fit Tests for the Gumbel Distribution with Type II right Censored data
Revista Colombiana de Estadística Diciembre 2012, volumen 35, no. 3, pp. 409 a 424 Goodness of Fit Tests for the Gumbel Distribution with Type II right Censored data Pruebas de bondad de ajuste para la
More informationb c d bidirectional link unidirectional link
Ï Ö Ð Æ ØÛÓÖ ¼ ¾¼¼½µ ß ½ ÊÓÙØ Ò Ð ÓÖ Ø Ñ ÓÖ Ï Ö Ð ÀÓ Æ ØÛÓÖ Û Ø ÍÒ Ö Ø ÓÒ Ð Ä Ò Ê Ú ÈÖ Ô ÖØÑ ÒØ Ó ÓÑÔÙØ Ö Ë Ò ÍÒ Ú Ö ØÝ Ó Ì Ü Ø ÐÐ Ê Ö ÓÒ Ì ¼ ¹¼ º ¹Ñ Ð Ö Ú ÔÙØ ÐÐ º Ù ÅÓ Ø Ó Ø ÖÓÙØ Ò Ð ÓÖ Ø Ñ ÓÖ Ó Ò ØÛÓÖ
More informationÄ Ò Ö Ò ÒØ ÖÓÔØ Ñ Þ Ø ÓÒÛ Ø ÔÔÐ Ø ÓÒ ÅÎ ½»ÅÅ ½ Å Ò ÑÙÑÓ Ø ÓÛÑÓ Ð Ò Ð ÓÖ Ø Ñ Ä ØÙÖ ½¼ ÒÒ¹ Ö Ø ËØÖ Ñ Ö ¾¼½ ¼ ¼¾ Ä ØÙÖ Ä Ò Ö Ò ÒØ ÖÓÔØ Ñ Þ Ø ÓÒÛ Ø ÔÔÐ Ø ÓÒ Å Ü ÑÙÑ ÓÛÑÓ Ð ÓÒ Ö ØÖ Ø Ø Ò Ò ØÛÓÖ Û Ø Ô Ô Ð Ò
More informationÑÔ Ö Ð Ø ÖÑ Ò ÒØ Ó ÑÔÐÓÝ Ê Ø Ò Ò Ø ÁÒÒÓÚ Ø ÓÒ Ì ÓÑ Û ÒØÖ ÓÖ ÙÖÓÔ Ò ÓÒÓÑ Ê Ö Ïµ ȺǺ ÓÜ ½¼ ½ ½ Å ÒÒ Ñ ÖÑ ÒÝ ¹Ñ Ð ÞÛ Þ Ûº ÆÓÚ Ñ Ö ¾¼¼¼ Á Û ÒØ ØÓ Ø Ò Å Ð Ö Ø À Ò ÓÖ ÑĐÙÒ Ò Ë Ò Ö ÓØØ Ð È Ø Ö Â ¹ Ó Ò Ù Å Ø
More informationProperties of Future Lifetime Distributions and Estimation
Properties of Future Lifetime Distributions and Estimation Harmanpreet Singh Kapoor and Kanchan Jain Abstract Distributional properties of continuous future lifetime of an individual aged x have been studied.
More information4) What are the uses of linear programming? $ òü Áb Á>±$T+> jóttø ÿ Á üjó»hê\t @$T?
ASSIGNMENT - 1, DEC - 2014. Paper I : PERSPECTIVES OF MANAGEMENT (DCM 01(NR)) 1) a) Administration ü]bõ\q. b) Strategy ep Vü ett. c) Decision tree ìs íj T eèø åett. d) Responsibility u
More informationHow To Make A Distributed System Transparent
Operating Systems Interface between the hardware and the rest: editors, compilers, database systems, application programs, your programs, etc. Allows portability, enables easier programming, The manager
More informationÌ Ö Ø ÅÝÈÓÐ È Ý Ç Ý Ý ÁÒ ØÝØÙØ ÞÝ Ö Ò ÏÝ ÓÙÖÒ ¾  ÒÙ Öݾ¼¼¾ ÍÒ Û Ö ÝØ ØÅ Ó ÃÓÔ ÖÒ ¹ÈÓÐ Ò Ø ÓÒ Ú ÒØÙÖÓÙ ÓÙÖÒ Ý Ó Ý Ý»Ó»ÒÓÙÒ ÔÐ Ý µ ÐÓÒ Ò Ú ÒØ ÙÐÓÖ ¹ÇÊÁ ÁÆÄ Ø ½ Ø ÒØ Ú Ä Ø Ò ÖÓÑ Ö Ç Ù Ì Æ ÏÇ ÇÊ Ø ÓÒ ÖÝÓ
More informationNON-COMPRESSED PGP MESSAGE L E N G T H M O D E C T B NAME LENGTH SEDP PACKET
ÁÑÔÐ Ñ ÒØ Ø ÓÒ Ó Ó Ò¹ Ô ÖØ ÜØ ØØ Ò Ø È È Ò ÒÙÈ Ã Ð Â ÐÐ ½ ÂÓÒ Ø Ò Ã ØÞ ¾ ÖÙ Ë Ò Ö ¾ ½ Ì ÓÒ ÓÑÔ ÒÝ Ð ÓÒÓÑÔ ÒݺÓÑ Ô ÖØÑ ÒØ Ó ÓÑÔÙØ Ö Ë Ò ÍÒ Ú Ö ØÝ Ó Å ÖÝÐ Ò ÓÐÐ È Ö µ ØÞ ºÙÑ º Ù ÓÙÒØ ÖÔ Ò ÁÒØ ÖÒ Ø Ë ÙÖ ØÝ
More informationDuration Analysis. Econometric Analysis. Dr. Keshab Bhattarai. April 4, 2011. Hull Univ. Business School
Duration Analysis Econometric Analysis Dr. Keshab Bhattarai Hull Univ. Business School April 4, 2011 Dr. Bhattarai (Hull Univ. Business School) Duration April 4, 2011 1 / 27 What is Duration Analysis?
More informationLecture 15 Introduction to Survival Analysis
Lecture 15 Introduction to Survival Analysis BIOST 515 February 26, 2004 BIOST 515, Lecture 15 Background In logistic regression, we were interested in studying how risk factors were associated with presence
More informationNonparametric adaptive age replacement with a one-cycle criterion
Nonparametric adaptive age replacement with a one-cycle criterion P. Coolen-Schrijner, F.P.A. Coolen Department of Mathematical Sciences University of Durham, Durham, DH1 3LE, UK e-mail: Pauline.Schrijner@durham.ac.uk
More informationCopyright (C) 1993,1994,1995 Hewlett Packard Company ALL RIGHTS RESERVED.
! " " # $ % & ' % ( ) * +, % -. / 0 1 ( 2 ) 3 ( 4 % 1 5 6 ( 7-8 $ % & 9 3 ( 2 : % ( ) 3 ( 0 1 -. % ; = >? @ A B C D E G > > I = @ L M M Copyright (C) 1993,1994,1995 ewlett Packard Company ALL IGS ESEVED.
More informationSoftware reliability analysis of laptop computers
Software reliability analysis of laptop computers W. Wang* and M. Pecht** *Salford Business School, University of Salford, UK, w.wang@salford.ac.uk ** PHM Centre of City University of Hong Kong, Hong Kong,
More informationPricing a Motor Extended Warranty With Limited Usage Cover
1/ 34 Pricing a Motor Extended Warranty With Limited Usage Cover By Fidelis T Musakwa 23 May 2013 (ASTIN Colloquium) 2/ 34 Outline 1.Introduction to motor warranties. 2.Research Problem 3.The Model 4.Case
More informationSUMAN DUVVURU STAT 567 PROJECT REPORT
SUMAN DUVVURU STAT 567 PROJECT REPORT SURVIVAL ANALYSIS OF HEROIN ADDICTS Background and introduction: Current illicit drug use among teens is continuing to increase in many countries around the world.
More informationDetection of changes in variance using binary segmentation and optimal partitioning
Detection of changes in variance using binary segmentation and optimal partitioning Christian Rohrbeck Abstract This work explores the performance of binary segmentation and optimal partitioning in the
More informationExclusive Right of Sale Listing Agreement FLORIDA ASSOCIATION OF REALTORS
Exclusive Right of Sale Listing Agreement FLORIDA ASSOCIATION OF REALTORS This Exclusive Right of Sale Listing Agreement ("Agreement") is between ("Seller") and ("Broker"). 1. AUTHORITY TO SELL PROPERTY
More informationÓÒ ÙÖ Ø ÓÒ ËÔ Å Ò ÓÖ Ù Ñ ÒØ Ò ÀÙÑ Ò È Ö ÓÖÑ Ò Ò Ì Ð ÓÔ Ö Ø ÓÒ Ì Áº ÁÚ Ò Ú Ò Îº ÄÙÑ Ð Ý ÊÓ ÓØ Ä ÍÒ Ú Ö ØÝ Ó Ï ÓÒ Ò¹Å ÓÒ Å ÓÒ Ï ÓÒ Ò ¼ ÍË ÓÖ ºÛ º Ù ØÖ Ø Ì Ô Ô Ö ÓÒ Ö Ò ÔÔÖÓ ØÓ ÓÔ Ö ØÓÖ¹ Ù Ö Ð Ø Ñ ÑÓØ ÓÒ
More informationExam C, Fall 2006 PRELIMINARY ANSWER KEY
Exam C, Fall 2006 PRELIMINARY ANSWER KEY Question # Answer Question # Answer 1 E 19 B 2 D 20 D 3 B 21 A 4 C 22 A 5 A 23 E 6 D 24 E 7 B 25 D 8 C 26 A 9 E 27 C 10 D 28 C 11 E 29 C 12 B 30 B 13 C 31 C 14
More informationNetworks of Collaboration in Oligopoly
TI 2000-092/1 Tinbergen Institute Discussion Paper Networks of Collaboration in Oligopoly Sanjeev Goyal Sumit Joshi Tinbergen Institute The Tinbergen Institute is the institute for economic research of
More informationVU Amsterdam. 6 Mbit/s ATM. UvA Amsterdam
Ì ØÖ ÙØ Ë Á ËÙÔ ÖÓÑÔÙØ Ö ÈÖÓ Ø À ÒÖ Ð Ê ÓÙÐ Ó Ò ÊÙØ Ö ÀÓ Ñ Ò Ö Ð Â Ó Ì ÐÓ Ã ÐÑ ÒÒ Â ÓÒ Å Ò ÊÓ Ú Ò Æ ÙÛÔÓÓÖØ ÂÓ Ò ÊÓÑ Ò ÄÙ Ê Ò Ñ ÓØ Ì Ñ ÊĐÙ Ð ÊÓÒ Ð Î Ð Ñ Ã Î Ö ØÓ Ô Ð Ò Ó ÖÓ ÐÐ ÒØ Ò Á ÓÖ ÃÙÞ Ù ÐÐ ÙÑ È ÖÖ
More informationÌÝÔ ¹ Ö Ø È ÖØ Ð Ú ÐÙ Ø ÓÒ ÇÐ Ú Ö ÒÚÝ ÊÁ Ë Ô ÖØÑ ÒØ Ó ÓÑÔÙØ Ö Ë ÍÒ Ú Ö ØÝ Ó Ö Ù Ù Ð ¼ ÆÝ ÅÙÒ Ã¹ ¼¼¼ Ö Ù ÒÑ Ö ¹Ñ Ð ÒÚÝ Ø Ô Ö º ÀÓÑ Ô ØØÔ»»ÛÛÛº Ö º» ÒÚÝ Ø Ô ØÖ Øº ÌÝÔ ¹ Ö Ø Ô ÖØ Ð Ú ÐÙ Ø ÓÒ Ù ÒÓÖÑ Ð Þ Ø
More informationÌÖ Ò ÓÒ Ø Ò Ø ÓÐ Ï Ö Ö Ò ÑÔ Ö Ð Ò ÐÝ Í Ò Ö Ø Ý Æ Ø Ò Ð Ò Å ØØ Û ÙÑ Ô ÖØÑ ÒØ Ó ÈÓÐ Ø Ð Ë Ò ÍÒ Ú Ö ØÝ Ó Ð ÓÖÒ Ë Ò Ó Ä ÂÓÐÐ ¾¼ Ù º Ù ½ ÈÖ Ô Ö ÓÖ Ð Ú ÖÝ Ø Ø ÏÓÖ ÓÔ ÓÒ ÌÖ Ò ÓÒ Ø Ó Ø ¾¼¼¼ ÈÊ ÂÓ ÒØ ÏÓÖ ÓÔ ÓÔ
More informationLink 1 Link 2 Sender. Link 1 Link 2. Receiver. Receiver. Sender
½ ÌÖ Ò ÔÓÖØ Ò Ê Ð¹Ø Ñ Î Ó ÓÚ Ö Ø ÁÒØ ÖÒ Ø ÐÐ Ò Ò ÔÔÖÓ Ô Ò ÏÙ ËØÙ ÒØ Å Ñ Ö Á Û Ì ÓÑ ÀÓÙ Å Ñ Ö Á Ò ¹É Ò Ò ÐÐÓÛ Á ØÖ Ø Ð Ú Ö Ò Ö Ð¹Ø Ñ Ú Ó ÓÚ Ö Ø ÁÒØ ÖÒ Ø Ò ÑÔÓÖØ ÒØ ÓÑÔÓÒ ÒØ Ó Ñ ÒÝ ÁÒØ ÖÒ Ø ÑÙÐØ Ñ Ô¹ ÔÐ
More informationA New Extension of the Exponential Distribution
Revista Colombiana de Estadística Junio 2014, volumen 37, no. 1, pp. 25 a 34 A New Extension of the Exponential Distribution Una nueva extensión de la distribución exponencial Yolanda M. Gómez 1,a, Heleno
More informationÝ Ø Ð Ñ ÔÖÓ Ò Û Ó Ø ÒÑ Ò Ù ØÑ ÒØÓ Ø Ò ÓÖÑ Ø ÓÒÓÒØ Ò Ò Ò Ñ Û Ø Ø ÑÓ ÙÑ Ò ÔØ Ø ÓÒÓ Ø Ò ÓÖÑ Ø ÓÒÓÒØ Ò Ò ÒØ ÖÔÖ Ø Ø ÓÒ Ñ ÔÖÓ Ò µ ÒØ ÖÔÖ Ø Ø ÓÒ Ñ Ò ÐÝ µ Ò Ñ Û Ø Ø ÑÓ ÙØÓÑ Ø Ì Ò Ð Ò Ó Ñ ÓÖ Ò Ø Ò ÑÓÚ Ò Ò ØÓÖ
More information**BEGINNING OF EXAMINATION** The annual number of claims for an insured has probability function: , 0 < q < 1.
**BEGINNING OF EXAMINATION** 1. You are given: (i) The annual number of claims for an insured has probability function: 3 p x q q x x ( ) = ( 1 ) 3 x, x = 0,1,, 3 (ii) The prior density is π ( q) = q,
More informationModeling the Claim Duration of Income Protection Insurance Policyholders Using Parametric Mixture Models
Modeling the Claim Duration of Income Protection Insurance Policyholders Using Parametric Mixture Models Abstract This paper considers the modeling of claim durations for existing claimants under income
More informationSANT GADGE BABA AMRAVATI UNIVERSITY
SANT GADGE BABA AMRAVATI UNIVERSITY Rule No.6 of 2010 Rules for Conducting Online Ph.D. Aptitude Test (PAT) for Degree of Doctor of Philosophy WHEREAS, it is expedient to frame the rules in respect of
More informationBias in the Estimation of Mean Reversion in Continuous-Time Lévy Processes
Bias in the Estimation of Mean Reversion in Continuous-Time Lévy Processes Yong Bao a, Aman Ullah b, Yun Wang c, and Jun Yu d a Purdue University, IN, USA b University of California, Riverside, CA, USA
More informationPerformance Analysis of RLC/MAC Protocol in General Packet Radio Service
Performance Analysis of RL/MA Protocol in General Packet Radio Service K. Premkumar and A. hockalingam Wireless Research Lab (http://wrl.ece.iisc.ernet.in) Ö ÖÚ Ø ÓÒ Department of Electrical ommunication
More informationWeb-based Supplementary Materials for Bayesian Effect Estimation. Accounting for Adjustment Uncertainty by Chi Wang, Giovanni
1 Web-based Supplementary Materials for Bayesian Effect Estimation Accounting for Adjustment Uncertainty by Chi Wang, Giovanni Parmigiani, and Francesca Dominici In Web Appendix A, we provide detailed
More informationAyersGTS (Internet) User Manual. Ayers Solutions Limited
A 12.0 AyersGTS (Internet) User Manual By Ayers Solutions Limited AyersGTS User Manual (Internet) v1.12.0 V!"#$% D&' D '&#(" V)*+ )-Jun-04 I%#'#&(,$-. V)*) 3-Aug-04 U-/&' / I0&1 " V)*4 4+-Dec-04 5// /
More informationPlanning social housing needs and housing market research training
êáóç³é³ï³ý ݳϳñ³Ý³ÛÇÝ ÐÇÙݳ¹ñ³Ù Social Housing Foundation Planning social housing needs and housing market research training Part 2 1 Main issues to address before starting project planning Who? Whom?
More informationProgram Proposal for a Minor
S15-1 Program Proposal for a Minor 1. Name of the proposed minor. Cyber Security 2. Name of the department(s) involved. Electrical and Computer Engineering 3. Name of contact person(s). Julie Rursch (jrursch@iastate.edu),
More informationErrata and updates for ASM Exam C/Exam 4 Manual (Sixteenth Edition) sorted by page
Errata for ASM Exam C/4 Study Manual (Sixteenth Edition) Sorted by Page 1 Errata and updates for ASM Exam C/Exam 4 Manual (Sixteenth Edition) sorted by page Practice exam 1:9, 1:22, 1:29, 9:5, and 10:8
More informationTests for exponentiality against the M and LM-classes of life distributions
Tests for exponentiality against the M and LM-classes of life distributions B. Klar Universität Karlsruhe Abstract This paper studies tests for exponentiality against the nonparametric classes M and LM
More informationCopyright 2010 Practical Law Publishing Limited and Practical Law Company, Inc.All Rights Reserved.
ÓÑÞ ÔÛ ÓßÎÕÛÌ ÒÙ ÉØßÌ ÝÑÓÐßÒ ÛÍ ÒÛÛÜ ÌÑ ÕÒÑÉ The advancements in mobile marketing technology are far outpacing the development of the regulations that govern it. Savvy marketers must understand not only
More informationLatin Alphabet special characters in Microsoft Word Article by: Stélios C. Alvarez 08
1 Latin Alphabet special characters in Microsoft Word Article by: Stélios C. Alvarez 08 For the purpose of this article, only accented letters and special characters from the Albanian, Basque, Bosnian,
More informationA Mobility Management Strategy for GPRS
A Mobility Management Strategy for GPRS Yi-Bing Lin and Shun-Ren Yang Abstract In General Packet Radio Service (GPRS), a mobile station (MS) is tracked at the cell level during packet transmission, and
More informationA Model of Optimum Tariff in Vehicle Fleet Insurance
A Model of Optimum Tariff in Vehicle Fleet Insurance. Bouhetala and F.Belhia and R.Salmi Statistics and Probability Department Bp, 3, El-Alia, USTHB, Bab-Ezzouar, Alger Algeria. Summary: An approach about
More informationA Load Balancing Mechanism with Verification
A Load Balancing Mechanism with Verification Daniel Grosu and Anthony T. Chronopoulos Department of Computer Science, University of Texas at San Antonio, 6900 N. Loop 1604 West, San Antonio, TX 78249 dgrosu,
More informationASCII control characters (character code 0-31)
ASCII control characters (character code 0-31) DEC HEX 0 00 NUL Null char 1 01 SOH Start of Heading 2 02 STX Start of Text 3 03 ETX End of Text 4 04 EOT End of Transmission
More informationPackage depend.truncation
Type Package Package depend.truncation May 28, 2015 Title Statistical Inference for Parametric and Semiparametric Models Based on Dependently Truncated Data Version 2.4 Date 2015-05-28 Author Takeshi Emura
More informationSurvival Models for Step-Stress Experiments with Lagged Effects
1 Survival Models for Step-Stress Experiments with Lagged Effects N. Kannan 1, D. Kundu 2, and N. Balakrishnan 3 1 Department of Management Science and Statistics, The University of Texas at San Antonio,
More informationÈÊÇ Ê ËË ÁÆ ÌÇÅÁ ÇÊ ÅÁ ÊÇË ÇÈ À Ð Ø Ø ÓÒ Ö Ø ĐÙÖ ÜÔ Ö Ñ ÒØ ÐÔ Ý Ö Å Ø Ñ Ø ¹Æ ØÙÖÛ Ò ØÐ Ò ÙÐØĐ Ø Ö ÍÒ Ú Ö ØĐ Ø Ù ÙÖ ÚÓÖ Ð Ø ÚÓÒ Öº Ö Öº Ò Øº Ö ÒÞ Âº Ð Ù ÙÖ ÆÓÚ Ñ Ö ¾¼¼¼ ÒÓÛÐ Ñ ÒØ Ì Ò ØÓ Ö Ø Ò Ë Ú Ö Ò ÓÖ
More informationË ÓÖعÖÙÒ Ö ØÙÖÒ ÖÓÙÒ Ø ÌÖ Ó ÓÖÔÓÖ Ø ÁÒ Ö ÓÒ Ø ÄÓÒ ÓÒ ËØÓ Ü Ò ËÝÐÚ Ò Ö Ö Ð Ò Ö ÓÖÝ ÂÓ Ò Å Ø Ø Ó Ò Á Ò ÌÓÒ º Ý Â ÒÙ ÖÝ ¾¼¼½ ØÖ Ø ÈÖ Ú ÓÙ ÛÓÖ Ü Ñ Ò Ø ÐÓÒ ¹ÖÙÒ ÔÖÓ Ø Ð ØÝ Ó ØÖ Ø Ñ Ñ Ò Ø ØÖ Ó ÓÑÔ ÒÝ Ö ØÓÖ
More informationCurriculum Vitae. Education Nanjing University, International Business School, Nanjing, P. R.China Bachelor of Arts in Economics, July 1994
Curriculum Vitae Zhining Hu Office Contact Information Department of Economics Gettysburg College Gettysburg, PA 17325 Office phone number: 717-337-6676 E-mail address: zhu@gettysburg.edu Education Nanjing
More informationŹ ÒØ Ð Ó Ö Ö Ø ØÙÖ ÓÖ Ø ÁÒØ Ö Ø ÓÒ Ó Ê ÓÒ Ò Ì Ò ÕÙ ÒØÓ ÈÖÓÓ ÈÐ ÒÒ Ò ÎÓÐ Ö ËÓÖ ÖØ Ø ÓÒ ÞÙÖ ÖÐ Ò ÙÒ Ö Ó ØÓÖ Ö ÁÒ Ò ÙÖÛ Ò Ø Ò Ö Æ ØÙÖÛ Ò ØÐ ¹Ì Ò Ò ÙÐØĐ Ø Á Ö ÍÒ Ú Ö ØĐ Ø Ë ÖÐ Ò Ë Ö ÖĐÙ Ò Þ Ñ Ö ¾¼¼½ Ò ÈÖÓ
More informationxzy){v } ~ 5 Vƒ y) ~! # " $ &%' #!! () ˆ ˆ &Šk Œ Ž Ž Œ Ž *,+.- / 012 3! 45 33 6!7 198 # :! & ŠkŠk Š $š2 š6œ1 ž ˆŸˆ & Š)œ1 ž 2 _ 6 & œ3 ˆœLŸˆ &Šž 6 ˆŸ œ1 &Š ' 6 ª & & 6 ž ˆŸ«k 1±²\³ kµ² µ0 0 9 ² ķ¹>² µ»º
More informationGamma Distribution Fitting
Chapter 552 Gamma Distribution Fitting Introduction This module fits the gamma probability distributions to a complete or censored set of individual or grouped data values. It outputs various statistics
More information1. Oblast rozvoj spolků a SU UK 1.1. Zvyšování kvalifikace Školení Zapojení do projektů Poradenství 1.2. Financování 1.2.1.
1. O b l a s t r o z v o j s p o l k a S U U K 1. 1. Z v y š o v á n í k v a l i f i k a c e Š k o l e n í o S t u d e n t s k á u n i e U n i v e r z i t y K a r l o v y ( d á l e j e n S U U K ) z í
More informationLecture 2 ESTIMATING THE SURVIVAL FUNCTION. One-sample nonparametric methods
Lecture 2 ESTIMATING THE SURVIVAL FUNCTION One-sample nonparametric methods There are commonly three methods for estimating a survivorship function S(t) = P (T > t) without resorting to parametric models:
More informationØ Å Ò Ò Û Ø ËØÖÙØÙÖ ÔØ Ò Æ ÙÖ Ð Æ ØÛÓÖ Ý Ä ÔÖ Ý ÑÑ Ò Ð ÓÓÒ Ëº ÀÓÒ µ Ø Ù Ñ ØØ Ò ÙÐÐ ÐÑ ÒØ Ó Ø Ö ÕÙ Ö Ñ ÒØ ÓÖ Ø Ö Ó ÓØÓÖ Ó È ÐÓ ÓÔ Ý Ë ÓÓÐ Ó ÓÑÔÙØ Ö Ë Ò Ò ËÓ ØÛ Ö Ò Ò Ö Ò ÅÓÒ ÍÒ Ú Ö ØÝ Å Ö ¾¼¼¼ ÌÓ ÑÑ ² Ì
More informationA Study of Direct Sequence Spread Spectrum Technique for Data Compression Purpose
3 ÒÃÈÖ ÉÒà ¹Ô ä àãç «Õà Çé¹Êà» Êà»ç µãñá ྠèí ÒÃãªé Ò¹ Ò éò¹ ÒúպÍÑ éíáùå Óà Ãѵ¹ì ÍÁÃÃÑ ÉÒ 1 ÁËÒÇÔ ÂÒÅÑÂà â¹âåâõ¾ãð ÍÁà ÅéÒ ¹ºØÃÕ ºÒ Á Øè ÃØ ÃØ à ¾Ï 10140 º Ñ ÂèÍ Ò¹ÇÔ Ñ¹Õéä éí ÔºÒÂ Ö ÇÔ Õ ÒÃ˹Öè «Öè
More informationInference on the parameters of the Weibull distribution using records
Statistics & Operations Research Transactions SORT 39 (1) January-June 2015, 3-18 ISSN: 1696-2281 eissn: 2013-8830 www.idescat.cat/sort/ Statistics & Operations Research c Institut d Estadstica de Catalunya
More informationÅ Ø ÓÑÔÙØ Ò ÓÒ ÓÑÑÓ ØÝ ÓÑÔÙØ Ö Ý Ö Ö ØÐÓÓ ÖØ Ø ÓÒ Ù Ñ ØØ Ò Ô ÖØ Ð ÙÐ ÐÐÑ ÒØ Ó Ø Ö ÕÙ Ö Ñ ÒØ ÓÖ Ø Ö Ó ÓØÓÖ Ó È ÐÓ ÓÔ Ý Ô ÖØÑ ÒØ Ó ÓÑÔÙØ Ö Ë Ò Æ Û ÓÖ ÍÒ Ú Ö ØÝ Å Ý ½ ÔÔÖÓÚ Ú Åº Ã Ñ ÌÓ ÑÝ Ñ ÐÝ Ò Ö Ò Û Ó
More informationTHE IMPACT OF NON FINANCIAL INNOVATIVE MANAGEMENT ACCOUNTING TECHNIQUES ON ECONOMIC ENVIRONMENT OF COMPANIES IN SANCTION SITUATION
THE IMPACT OF NON FINANCIAL INNOVATIVE MANAGEMENT ACCOUNTING TECHNIQUES ON ECONOMIC ENVIRONMENT OF COMPANIES IN SANCTION SITUATION Mohammad Reza SOHRABI PhD student at YSU Department of economics Keywords:
More informationMicro-level stochastic loss reserving for general insurance
Faculty of Business and Economics Micro-level stochastic loss reserving for general insurance Katrien Antonio, Richard Plat DEPARTMENT OF ACCOUNTANCY, FINANCE AND INSURANCE (AFI) AFI_1270 Micro level stochastic
More informationÏ Ö Ð ÁÒØ ÖÒ Ø Ø Û Ý ÏÁÆ µ ÓÖ Ì ÁÒØ ÖÒ Ø Ò Ð Ì Ò Ð Ê ÔÓÖØ Ö ÒØ ÆÓ ¼ ¹ ¹ ¹ ½ ÇØÓ Ö ¾¾ ¾¼¼½ ÈÖ Ô Ö ÓÖ Ò Ú Ò Ê Ö ÈÖÓ Ø ÒÝ»ÁÌÇ ¼½ ÆÓÖØ Ö Ü Ö Ú ÖÐ Ò ØÓÒ Î ¾¾¾¼ ¹½ ½ ËÙ Ñ ØØ Ý Ì Ê ÒØ Ó Ì ÍÒ Ú Ö ØÝ Ó Ð ÓÖÒ Ë
More informationPublication List. Chen Zehua Department of Statistics & Applied Probability National University of Singapore
Publication List Chen Zehua Department of Statistics & Applied Probability National University of Singapore Publications Journal Papers 1. Y. He and Z. Chen (2014). A sequential procedure for feature selection
More informationEntry of Foreign Life Insurers in China: A Survival Analysis
Entry of Foreign Life Insurers in China: A Survival Analysis M.K. Leung * This paper uses survival analysis to examine the firm-specific factors determining the decision of a foreign firm to establish
More informationCONTINUED FRACTIONS AND FACTORING. Niels Lauritzen
CONTINUED FRACTIONS AND FACTORING Niels Lauritzen ii NIELS LAURITZEN DEPARTMENT OF MATHEMATICAL SCIENCES UNIVERSITY OF AARHUS, DENMARK EMAIL: niels@imf.au.dk URL: http://home.imf.au.dk/niels/ Contents
More informationMemory Efficient All-Solutions SAT Solver and its Application for Reachability Analysis
Memory Efficient All-Solutions SAT Solver and its Application for Reachability Analysis Orna Grumberg Assaf Schuster Avi Yadgar Computer Science Department, Technion, Haifa, Israel Abstract This work presents
More informationÙÒØ ÓÒ Ð ÈÖÓ Ö ÑÑ Ò ÈÖÓ Ö Ñ ÌÖ Ò ÓÖÑ Ø ÓÒ Ò ÓÑÔ Ð Ö ÓÒ ØÖÙØ ÓÒ ÓÚ Ö Ä Ñ ÔÖ Ò Ð Ô Ô ÐÓ ÓÔ Ó ÙÖ Ø Ñ Ð Ñ Ø Ò ÅÙ ÙÑ À Ö¹ Ñ Ø ÙÑ Ö Ò ÙÖØ ½ Ôº º ÙÒØ ÓÒ Ð ÈÖÓ Ö ÑÑ Ò ÈÖÓ Ö Ñ ÌÖ Ò ÓÖÑ Ø ÓÒ Ò ÓÑÔ Ð Ö ÓÒ ØÖÙØ ÓÒ
More informationFor the IRS There's No EZ Fix
For the IRS There's No EZ Fix - business unit accountability critical to complex project; c... Page 1 of 14 Apr. 1, 2004 Iss PROJECT MANAGEMENT For the IRS There's No EZ Fix By assembling a star-studded
More informationScaling Question Answering to the Web
Scaling Question Answering to the Web Cody C. T. Kwok University of Washington Seattle, WA, USA ctkwok@cs. washington.edu Oren Etzioni University of Washington Seattle, WA, USA etzioni@cs. washington.edu
More informationBASE: Using Abstraction to Improve Fault Tolerance
BASE: Using Abstraction to Improve Fault Tolerance Rodrigo Rodrigues Ý, Miguel Castro Ü, and Barbara Liskov Ý Ý MIT Laboratory for Computer Science 2 Technology Sq., Cambridge MA 239, USA Ü Microsoft Research
More informationHowHow to Choose a Good Stock Broker For 2008
Î Ð Ö Ö ÐÐ Ò ÍÒ Ú Ö Ø ÊÓÑ ÌÓÖ Î Ö Ø ÊÓÑ Á¹¼¼½ Ö ÐÐ Ò ÙÒ ÖÓÑ ¾º Ø ÝÒ Ñ ÄÓ Ð Ò Ò ÓÒ Ï ¹ ÖÚ Ö ËÝ Ø Ñ È Ð Ô Ëº Ù Á Š̺º Ï Ø ÓÒ Ê Ö ÒØ Ö ÓÖ ØÓÛÒ À Ø Æ ½¼ Ô ÝÙÙ º ѺÓÑ Å Ð ÓÐ ÒÒ ÍÒ Ú Ö Ø ÅÓ Ò Ê Ó Ñ Ð ÅÓ Ò
More informationFrom Sparse Approximation to Forecast of Intraday Load Curves
From Sparse Approximation to Forecast of Intraday Load Curves Mathilde Mougeot Joint work with D. Picard, K. Tribouley (P7)& V. Lefieux, L. Teyssier-Maillard (RTE) 1/43 Electrical Consumption Time series
More informationSurvival Distributions, Hazard Functions, Cumulative Hazards
Week 1 Survival Distributions, Hazard Functions, Cumulative Hazards 1.1 Definitions: The goals of this unit are to introduce notation, discuss ways of probabilistically describing the distribution of a
More informationFuzzy Measures and integrals for evaluating strategies
Fuzzy Measures and integrals for evaluating strategies Yasuo Narukawa Toho Gakuen, 3-1-10 Naka, Kunitachi, Tokyo, 186-0004 Japan E-mail: narukawa@d4.dion.ne.jp Vicenç Torra IIIA-CSIC, Campus UAB s/n 08193
More informationRESEARCH INTERESTS Modeling and Simulation, Complex Systems, Biofabrication, Bioinformatics
FENG GU Assistant Professor of Computer Science College of Staten Island, City University of New York 2800 Victory Boulevard, Staten Island, NY 10314 Doctoral Faculty of Computer Science Graduate Center
More informationUniversitat Autònoma de Barcelona Ö ÏÓÖ Ø Ø ÓÒ Ò ÝÒ Ñ ÅÓ Ð ØÓ Ø Ò ÓÖÓÒ ÖÝ ÌÖ Ò ÐÝ ÖØ Ø ÓÒ Ù Ñ ØØ Ý Ê Ö Ó ÌÓÐ Ó ÅÓÖ Ð Ø ÍÒ Ú Ö Ø Ø ÙØ ÓÒÓÑ Ö ÐÓÒ ØÓ ÙÐ Ð Ø Ö Ó ÓØÓÖ Ò ÁÒ ÓÖÑ Ø º ÐÐ Ø ÖÖ ÂÙÒ ½ ¾¼¼½ Ö ØÓÖ
More informationÐ ØÖÓÒ ÆÓØ Ò Ì ÓÖ Ø Ð ÓÑÔÙØ Ö Ë Ò ÆÓº ¾ ¾¼¼½µ ÍÊÄ ØØÔ»»ÛÛÛº Ð Ú ÖºÒлÐÓ Ø» ÒØ»ÚÓÐÙÑ º ØÑÐ ½ Ô ÓÐÐ Ø Ò Ò Ò ÐÝÞ Ò Ø ÖÓÑ ØÖ ÙØ ÓÒØÖÓÐ ÈÖÓ Ö Ñ Ú ÃÓÖØ Ò ÑÔ Ò ÌÓ Å Ð Ñ Å ØÖ ÁÒº»ÌÊ Ä ½¼½¾ À ÖÙÐ ÀÓÙ ØÓÒ Ì ÍË ¼
More informationARC Centre of Excellence in Population Ageing Research. Working Paper 2011/3
ARC Centre of Excellence in Population ing Research Working Paper / Heterogeneity of Australian Population Mortality and Implications for a Viable Life Annuity Market Shu Su and Michael Sherris* * Su is
More informationDistribution (Weibull) Fitting
Chapter 550 Distribution (Weibull) Fitting Introduction This procedure estimates the parameters of the exponential, extreme value, logistic, log-logistic, lognormal, normal, and Weibull probability distributions
More informationÆ Û È Ö Ñ ÓÖ Ù Ó ÓÒ Ö Ò Ò ÓÒ ÎÓ ÓÚ Ö ÁÈ ÎÓÁȵ Ì ËÙ Ñ ØØ ÓÖ Ø Ö Ó ÓØÓÖ Ó È ÐÓ ÓÔ Ý Ò Ø ÙÐØÝ Ó Ò Ò Ö Ò Ý Êº Î Ò Ø ÈÖ ÒØÖ ÓÖ Ð ØÖÓÒ Ò Ò Ì ÒÓÐÓ Ý ÁÒ Ò ÁÒ Ø ØÙØ Ó Ë Ò Ò ÐÓÖ ß ¼ ¼½¾ ÁÒ ÂÙÐÝ ¾¼¼ ÓÒ ÓÒ Á ÒÓÛ Ø
More informationAn international comparison of energy and climate change policies impacting energy intensive industries in selected countries. Table of Contents.
Table of Contents Page i Figures ii iii Tables iv 1 2 3 4 5 6 7 8 9 Converted 8 !! >?@AB CD EC CC FGF HIJA "#$%& '%($& )&*&% +,--$&.,/012 345 61%7&/08/&%91:1/7&%2 ';&
More information