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There are two topics in this dissertation. The first topic is 'Smoothing Parameter Selection in Nonparametric Generalized Linear Models via Sixth-order Laplace Approximation' and the second topic is 'Smoothing Spline-based Score Tests for Proportional Hazards Models'.We present a new approach...
Persistent link: https://www.econbiz.de/10009431282
In many scientific studies, the response variable bears a generalized nonlinear regression relationship with a certain covariate of interest, which may, however, be confounded by other covariates with unknown functional form. We propose a new class of models, the partly parametric generalized...
Persistent link: https://www.econbiz.de/10009466085
semiparametric statistical methods. This article describes the new Stata command haplologit, which implements efficient profile …-likelihood semiparametric methods for fitting gene-environment models in the very important special cases of a rare disease, a single candidate …
Persistent link: https://www.econbiz.de/10005583263
Nonconstancy of the bispectrum of a time series has been taken as a measure of non-Gaussianity and nonlinear serial dependence in a stochastic process by Subba Rao and Gabr (1980) and by Hinich (1982), leading to Hinich's statistical test of the null hypothesis of a linear generating mechanism...
Persistent link: https://www.econbiz.de/10005511878
A widely used filter to extract a signal in a time series, in particular in the business cycle analysis, is the Hodrick-Prescott filter. The model that underlies the filter considers the data series as the sum of two unobserved component (signal and non signal) and a smoothing parameter which...
Persistent link: https://www.econbiz.de/10005407924
In business cycle research, smoothing data is an essential step in that it can influence the extent to which model-generated moments stand up to their empirical counterparts. To demonstrate this idea, we compare the results of McDermott’s (1997) modified HP-filter with the conventional...
Persistent link: https://www.econbiz.de/10011257993
Nonparametric density estimation is of great importance when econometricians want to model the probabilistic or stochastic structure of a data set. This comprehensive review summarizes the most important theoretical aspects of kernel density estimation and provides an extensive description of...
Persistent link: https://www.econbiz.de/10010837162
We consider the estimation problem of conditional quantile when multi-dimensional covariates are involved. To overcome the “curse of dimensionality” yet retain model flexibility, we propose two partially linear models for conditional quantiles: partially linear single-index models (QPLSIM)...
Persistent link: https://www.econbiz.de/10011056482
Based on sero-prevalence data of rubella, mumps in the UK and varicella in Belgium, we show how the force of infection, the age-specific rate at which susceptible individuals contract infection, can be estimated using generalized linear mixed models (McCulloch & Searle, 2001). Modelling the...
Persistent link: https://www.econbiz.de/10005639688
Persistent link: https://www.econbiz.de/10005598682