Mathematical Statistics: An Introduction to Likelihood Based Inference

Specifications

Book Description

Presents a unified approach to parametric estimation; hypothesis testing; confidence intervals; and statistical modeling; which are uniquely based on the likelihood function. This ebook; Mathematical Statistics: An Introduction to Likelihood Based Inference (PDF); addresses mathematical statistics for first year graduate and upper-undergraduates students; tying chapters on estimation; hypothesis testing; confidence intervals; and statistical models together to present a unifying focus on the likelihood function. It also emphasizes the important ideas in statistical modeling; such as exponential family distributions; sufficiency; and large sample properties. Rossi’s Mathematical Statistics: An Introduction to Likelihood Based Inference PDF makes advanced topics accessible and understandable and covers many topics in more depth than typical mathematical statistics textbooks. It includes numerous case studies; great examples; a large number of exercises ranging from drill and skill to extremely difficult problems; and many of the important theorems of mathematical statistics along with their proofs.

In addition to the connected chapters mentioned above; Mathematical Statistics covers likelihood-based estimation; with emphasis on multidimensional parameter spaces and range dependent support. It also includes a chapter on confidence intervals; which contains examples of exact confidence intervals along with the standard large sample confidence intervals based on the MLE’s and bootstrap confidence intervals. There’s also a chapter on parametric statistical models featuring sections on Poisson regression; non-iid observations; logistic regression; linear regression; and linear models.

• Features good examples; problems; and solutions
• Includes sections on Bayesian estimation and credible intervals
• Prepares college students with the tools needed to be successful in their future work in statistics data science
• Emphasizes the important ideas to statistical modeling; such as exponential family distribution; sufficiency; and large sample properties
• Includes practical case studies including real-life data collected from the Donner party; Yellowstone National Park; and the Titanic voyage

Mathematical Statistics: An Introduction to Likelihood Based Inference is an ideal etextbook for graduate and upper-undergraduate courses in mathematical statistics; probability; and/or statistical inference.