Large Sample Methods in Statistics: An Introduction with ApplicationsCRC Press, 4 de abr. de 1994 - 400 páginas This text bridges the gap between sound theoretcial developments and practical, fruitful methodology by providing solid justification for standard symptotic statistical methods. It contains a unified survey of standard large sample theory and provides access to more complex statistical models that arise in diverse practical applications. |
Conteúdo
Weak Convergence and Central Limit Theorems | 98 |
Large Sample Behavior of Empirical Distributions and | 155 |
Asymptotic Behavior of Estimators and Test Statistics | 201 |
Large Sample Theory for Categorical Data Models | 247 |
Large Sample Theory for Regression Models | 273 |
Invariance Principles in Large Sample Theory | 327 |
References | 371 |
| 377 | |
Outras edições - Ver todos
Large Sample Methods in Statistics (1994): An Introduction with Applications Pranab K. Sen,Julio M. Singer Visualização parcial - 2017 |
Large Sample Methods in Statistics (1994): An Introduction with Applications Pranab K. Sen,Julio M. Singer Prévia não disponível - 2017 |
Revival: Large Sample Methods in Statistics (1994) Pranab K. Sen,Julio M. Singer Prévia não disponível - 2019 |
Termos e frases comuns
applications assume asymptotic distribution asymptotic normality asymptotic properties Borel-Cantelli Lemma Central Limit Theorem Chapter characteristic function conclude context continuous convergence in probability corresponding defined definition denote density function distribution function equations estimator Example Exercise exists exponential finite Fn(x function F given hence holds implies independent r.v.'s Khintchine Kolmogorov Large Numbers large sample theory Law of Large Let X1 likelihood linear model log Ln log Ln(0 M-estimators martingale matrix methods mode of convergence multivariate nonparametric normal distribution observe obtain order statistics parameter probability inequalities problem Proof random variables regularity conditions reverse martingale sample quantiles Section sequence setup Slutsky Theorem 3.4.2 stochastic convergence submartingale T₂ termed test statistics U-statistics variance vector verify weak convergence write Xn:n Y₁ zero mean
Referências a este livro
Applied Multivariate Statistics with SAS Software, Second Edition Ravindra Khattree,Dayanand N. Naik Prévia não disponível - 2000 |
Foundations of Statistical Analyses and Applications with SAS Michael Falk,Frank Marohn,Bernward Tewes Visualização parcial - 2002 |