國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Statistical inference in financial a...

Brouste, Alexandre,

Statistical inference in financial and insurance mathematics with R /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Statistical inference in financial and insurance mathematics with R /Alexandre Brouste.
作者:	Brouste, Alexandre,
面頁冊數:	1 online resource
標題:	FinanceMathematical models.
電子資源:	https://www.sciencedirect.com/science/book/9781785480836
ISBN:	9780081012611$q(electronic bk.)

Statistical inference in financial and insurance mathematics with R /
Brouste, Alexandre,

Statistical inference in financial and insurance mathematics with R /Alexandre Brouste. - 1 online resource - Optimization in insurance and finance set. - Optimization in insurance and finance set..

Includes bibliographical references and index.

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.

ISBN: 9780081012611$q(electronic bk.)Subjects--Topical Terms:

183782
Finance
--Mathematical models.Index Terms--Genre/Form:

214472
Electronic books.

LC Class. No.: HG106

Dewey Class. No.: 332.0151852

Statistical inference in financial and insurance mathematics with R /
LDR:02230cmm a2200289 i 4500 001 561852
006 m o d
007 cr cnu|||unuuu
008 200213s2018 enk ob 001 0 eng d
020 $a 9780081012611$q(electronic bk.)
020 $a 0081012616$q(electronic bk.)
020 $a 9781785480836
035 $a (OCoLC)1013889091
035 $a els69900589
040 $a N $b eng $e rda $e pn $c N $d IDEBK $d EBLCP $d N $d OCLCF $d OPELS $d UAB $d GZM $d DKU $d SNK
041 0 $a eng
050 4 $a HG106
082 0 4 $a 332.0151852 $2 23
100 1 $a Brouste, Alexandre, $e author. $3 846512
245 1 0 $a Statistical inference in financial and insurance mathematics with R / $c Alexandre Brouste.
264 1 $a London : $b ISTE Press Ltd ; $a Kidlington, Oxford : $b Elsevier Ltd., $c 2018.
300 $a 1 online resource
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
490 1 $a Optimization in insurance and finance set
504 $a Includes bibliographical references and index.
520 $a 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.
650 0 $a Finance $x Mathematical models. $3 183782
650 0 $a Insurance $x Mathematical models. $3 183042
655 4 $a Electronic books. $2 local. $3 214472
830 0 $a Optimization in insurance and finance set. $3 839628
856 4 0 $u https://www.sciencedirect.com/science/book/9781785480836