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Statistical Inference in Financial and Insurance Mathematics with R (Hardcover)
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Statistical Inference in Financial and Insurance Mathematics with R (Hardcover)
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Finance and insurance companies are facing a wide range of
parametric statistical problems. Statistical experiments generated
by a sample of independent and identically distributed random
variables are frequent and well understood, especially those
consisting of probability measures of an exponential type. However,
the aforementioned applications also offer non-classical
experiments implying observation samples of independent but not
identically distributed random variables or even dependent random
variables. Three examples of such experiments are treated in this
book. First, the Generalized Linear Models are studied. They extend
the standard regression model to non-Gaussian distributions.
Statistical experiments with Markov chains are considered next.
Finally, various statistical experiments generated by fractional
Gaussian noise are also described. In this book, asymptotic
properties of several sequences of estimators are detailed. The
notion of asymptotical efficiency is discussed for the different
statistical experiments considered in order to give the proper
sense of estimation risk. Eighty examples and computations with R
software are given throughout the text.
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