ALLAY 发表于 2025-3-26 21:54:39
Statistical Foundations of Actuarial Learning and its Applicationsaerial 发表于 2025-3-27 01:31:33
http://reply.papertrans.cn/88/8765/876418/876418_32.png过于平凡 发表于 2025-3-27 06:18:54
http://reply.papertrans.cn/88/8765/876418/876418_33.pngAWRY 发表于 2025-3-27 10:00:05
2523-3262 achine learning methods.Discusses the state-of-the-art in prThis open access book discusses the statistical modeling of insurance problems, a process which comprises data collection, data analysis and statistical model building to forecast insured events that may happen in the future. It presents thTHROB 发表于 2025-3-27 16:59:34
Exponential Dispersion Family,important classes of distribution functions for regression modeling. They include, among others, the Gaussian, the binomial, the Poisson, the gamma, the inverse Gaussian distributions, as well as Tweedie’s models. We introduce these families of distribution functions, discuss their properties and prechnic 发表于 2025-3-27 17:57:49
http://reply.papertrans.cn/88/8765/876418/876418_36.pngSPURN 发表于 2025-3-27 23:23:02
http://reply.papertrans.cn/88/8765/876418/876418_37.png碎片 发表于 2025-3-28 05:55:26
http://reply.papertrans.cn/88/8765/876418/876418_38.pngLOPE 发表于 2025-3-28 06:20:57
Bayesian Methods, Regularization and Expectation-Maximization,arlo (MCMC) method for model fitting. We discuss regularization of regression models such as ridge and LASSO regularization, which has a Bayesian interpretation, and we consider the Expectation-Maximization (EM) algorithm. The EM algorithm is a general purpose tool that can handle incomplete data seadulterant 发表于 2025-3-28 11:51:05
http://reply.papertrans.cn/88/8765/876418/876418_40.png