Statistical Inference in Linear Models

Linear models are statistical models that play a crucial role in several fields of science and are of practical importance in statistics. The most typical type is the linear regression model. Many phenomena, such as those in biology, medicine, economics, management, geology, meteorology, agriculture...

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Μορφή:	Online
Γλώσσα:	Αγγλικά
Έκδοση:	MDPI - Multidisciplinary Digital Publishing Institute 2024
Θέματα:	exponential-logarithmic distribution T-X transformation moments entropy maximum likelihood estimation simulation data sciences Farlie Gumbel Morgenstern (FGM) copula generalized half-logistic distribution (GHLD) reliability parameter Monte Carlo simulation statistical properties household financial affordability Bayesian inference hazard-based regression model survival analysis accelerated hazard model generalized log-logistic distribution crossover survival curves censored data COVID-19 bounded distribution estimation methods Cauchy regression bivariate correlation likelihood ratio test maximum likelihood estimators pseudo-Poisson Kalman filter VAR GARCH quantile regression modal regression biomedical unit distribution skewed data aggregate claims distribution compound CMP regression model generalized linear models prediction intervals negative binomial distribution computation R package sum of negative binomial variables sine function Weibull distribution hazard function solar irradiation quantile quantile function median rankit population mean thema EDItEUR::U Computing and Information Technology::UY Computer science
Διαθέσιμο Online:	ONIX_20240514_9783725802579_196
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Statistical Inference in Linear Models

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