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Betensky, R and Finkelstein, D (1999) A non parametric maximum likelihood estimator for bivariate interval censored data Statistics in Medicine, 18, 3089 3100 Blossfeld, H and Mills, M (2003) A causal approach to interrelated family events Proceedings of Statistics Canada Symposium 2002: Modelling Survey Data for Social and Economic Research Ottawa: Statistics Canada Braun, J, Duchesne, T and Stafford, J (2005) Local likelihood density estimation for interval censored data Canadian Journal of Statistics, 33, 39 60 Breunig, R V (2001) Density estimation for clustered data Econometric Reviews, 20, 353 367 Buskirk, T and Lohr, S (2005) Asymptotic properties of kernel density estimation with complex survey data Journal of Statistical Planning and Inference, 128, 165 190 Charles, K K and Stephens, M J (2004) Job displacement, disability and divorce Journal of Labour Economics, 22, 489 522 Cook, R J, Zeng, L and Lee, K (2008).



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as polynomial or non-deterministic polynomial. Polynomial problems require polynomial algorithms that grow linearly in terms of memory and time or at worst they grow in polynomial time. Non-deterministic polynomial (NP) problems are characterized by exponential growth. Unfortunately, a number of problems in bioinformatics fall in the NP class.

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A multistate model for bivariate interval censored failure time data Biometrics, 64, 1100 1109 Duchesne, T and Stafford, J (2001) A kernel density estimate for interval censored data Technical Report No 0106, University of Toronto Gentleman, R and Geyer, C (1994) Maximum likelihood for interval censored data: consistency and computation Biometrika, 81, 618 623 Hjort, N L and Jones, M C (1996) Locally parametric nonparametric density estimation Annals of Statistics, 24, 1619 1647 Huang, J (2003) Unemployment and family behavior in Taiwan Journal of Family and Economic Issues, 24, 27 48 Huttenlocher, J, Hedges, L and Bradburn, N M (1990) Reports of elapsed time: Bounding and rounding processes in estimation Journal of Experimental Psychology: Learning, Memory and Cognition, 16, 196 213 Jahoda, M, Lazarsfeld, P F and Zeisel, H (1933) Marienthal The Sociography of an Unemployed Community Chicago: Aldine Atherton Inc Jewell, N, van der Laan, M.

[Sin99] [SIR01]

The pinouts of the IC itself are seen in Figure 6-9.

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and Lei, X (2005) Bivariate current status data with univariate monitoring times Biometrika, 92, 847 862 Larry, J L T and Catlin, G (1995) Sampling design of the National Population Health Survey In Health Reports (vol 7, pp 29 38) Ottawa: Statistics Canada Lawless, J (2003) Event history analysis and longitudinal surveys In R Chambers and C J Skinner (Eds), Analysis of Survey Data (pp 221 243) New York: John Wiley & Sons, Inc Li, L, Watkins, T and Yu, Q (1997) An EM algorithm for smoothing the self consistent estimator of survival functions with interval censored data Scandinavian Journal of Statistics, 24, 531 542 Loader, C R (1996) Local likelihood density estimation Annals of Statistics, 24, 1602 1618 Neter, J and Waksberg, J (1964) A study of response errors in expenditures data from household interviews Journal of the American Statistical Association, 59, 17 55 Pantoja Galicia, N (2007).

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Lemma 7.5 If[N(x), W(x)] is an irreducible solution to the interpolation(k) problem and [M(x), V(x)] is another solution such that rank[N(x), W(x)] rank[M(x), V(x)] 5 2k, then [M(x), V(x)] can be reduced to [N(x), W(x)].

Interval censoring and longitudinal survey data PhD Thesis, Department of Statistics and Actuarial Science, University of Waterloo Pantoja Galicia, N, Thompson, M E and Kovacevic, M (2005) A bivariate density estimation approach using data from the survey of labour and income dynamics: an example of testing for temporal order of job loss and divorce Proceedings of the Survey Methods Section, Statistical Society of Canada Annual Meeting, June 2005, at http://wwwsscca/survey/ documents/SSC2005_N_Pantoja Galiciapdf Rao, J and Wu, C (1988) Resampling inference with complex survey data Journal of the American Statistical Association, 83, 231 241 Rao, J, Wu, C and Yue, K (1992) Some recent work on resampling methods for complex survey data Survey Methodology, 18, 209 217 Rust, K and Rao, J (1996) Variance estimation for complex surveys using replication techniques Statistical Methods in Medical Research, 5, 283 310..

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