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

Analytical methods in statisticsAMIS...

(1998 :)

Analytical methods in statisticsAMISTAT, Liberec, Czech Republic, September 2019 /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Analytical methods in statisticsedited by Matus Maciak, Michal Pesta, Martin Schindler.
其他題名:	AMISTAT, Liberec, Czech Republic, September 2019 /
其他作者:	Maciak, Matus.
團體作者:
出版者:	Cham :Springer International Publishing :2020.
面頁冊數:	x, 156 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Mathematical statistics
電子資源:	https://doi.org/10.1007/978-3-030-48814-7
ISBN:	9783030488147$q(electronic bk.)

Analytical methods in statisticsAMISTAT, Liberec, Czech Republic, September 2019 /
Analytical methods in statisticsAMISTAT, Liberec, Czech Republic, September 2019 /[electronic resource] :edited by Matus Maciak, Michal Pesta, Martin Schindler. - Cham :Springer International Publishing :2020. - x, 156 p. :ill., digital ;24 cm. - Springer proceedings in mathematics & statistics,v.3292194-1009 ;. - Springer proceedings in mathematics & statistics ;v.19..

Preface -- Y. Guney, J. Jureckova and O. Arslan, Averaged Autoregression Quantiles in Autoregressive Model -- J. Kalina and P. Vidnerova, Regression Neural Networks with a Highly Robust Loss Function -- H. L. Koul and P. Geng, Weighted Empirical Minimum Distance Estimators in Berkson Measurement Error Regression Models -- M. Maciak, M. Pesta and S. Vitali, Implied Volatility Surface Estimation via Quantile Regularization -- I. Mizera, A remark on the Grenander estimator -- U. Radojicic and K. Nordhausen, Non-Gaussian Component Analysis: Testing the Dimension of the Signal Subspace -- P. Vidnerova, J. Kalina and Y. Guney, A Comparison of Robust Model Choice Criteria within a Metalearning Study -- S. Zwanzig and R. Ahmad, On Parameter Estimation for High Dimensional Errors-in-Variables Models.

This book collects peer-reviewed contributions on modern statistical methods and topics, stemming from the third workshop on Analytical Methods in Statistics, AMISTAT 2019, held in Liberec, Czech Republic, on September 16-19, 2019. Real-life problems demand statistical solutions, which in turn require new and profound mathematical methods. As such, the book is not only a collection of solved problems but also a source of new methods and their practical extensions. The authoritative contributions focus on analytical methods in statistics, asymptotics, estimation and Fisher information, robustness, stochastic models and inequalities, and other related fields; further, they address e.g. average autoregression quantiles, neural networks, weighted empirical minimum distance estimators, implied volatility surface estimation, the Grenander estimator, non-Gaussian component analysis, meta learning, and high-dimensional errors-in-variables models.

ISBN: 9783030488147$q(electronic bk.)

Standard No.: 10.1007/978-3-030-48814-7doiSubjects--Topical Terms:

182294
Mathematical statistics

LC Class. No.: QA276.A1 / A535 2019

Dewey Class. No.: 519.5

Analytical methods in statisticsAMISTAT, Liberec, Czech Republic, September 2019 /
LDR:02888nmm a2200337 a 4500 001 583757
003 DE-He213
005 20201123114932.0
006 m d
007 cr nn 008maaau
008 210202s2020 sz s 0 eng d
020 $a 9783030488147$q(electronic bk.)
020 $a 9783030488130$q(paper)
024 7 $a 10.1007/978-3-030-48814-7 $2 doi
035 $a 978-3-030-48814-7
040 $a GP $c GP
041 0 $a eng
050 4 $a QA276.A1 $b A535 2019
072 7 $a PBT $2 bicssc
072 7 $a MAT029000 $2 bisacsh
072 7 $a PBT $2 thema
082 0 4 $a 519.5 $2 23
090 $a QA276.A1 $b A517 2019
111 2 $n (3rd : $d 1998 : $c Amsterdam, Netherlands) $3 194767
245 1 0 $a Analytical methods in statistics $h [electronic resource] : $b AMISTAT, Liberec, Czech Republic, September 2019 / $c edited by Matus Maciak, Michal Pesta, Martin Schindler.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a x, 156 p. : $b ill., digital ; $c 24 cm.
490 1 $a Springer proceedings in mathematics & statistics, $x 2194-1009 ; $v v.329
505 0 $a Preface -- Y. Guney, J. Jureckova and O. Arslan, Averaged Autoregression Quantiles in Autoregressive Model -- J. Kalina and P. Vidnerova, Regression Neural Networks with a Highly Robust Loss Function -- H. L. Koul and P. Geng, Weighted Empirical Minimum Distance Estimators in Berkson Measurement Error Regression Models -- M. Maciak, M. Pesta and S. Vitali, Implied Volatility Surface Estimation via Quantile Regularization -- I. Mizera, A remark on the Grenander estimator -- U. Radojicic and K. Nordhausen, Non-Gaussian Component Analysis: Testing the Dimension of the Signal Subspace -- P. Vidnerova, J. Kalina and Y. Guney, A Comparison of Robust Model Choice Criteria within a Metalearning Study -- S. Zwanzig and R. Ahmad, On Parameter Estimation for High Dimensional Errors-in-Variables Models.
520 $a This book collects peer-reviewed contributions on modern statistical methods and topics, stemming from the third workshop on Analytical Methods in Statistics, AMISTAT 2019, held in Liberec, Czech Republic, on September 16-19, 2019. Real-life problems demand statistical solutions, which in turn require new and profound mathematical methods. As such, the book is not only a collection of solved problems but also a source of new methods and their practical extensions. The authoritative contributions focus on analytical methods in statistics, asymptotics, estimation and Fisher information, robustness, stochastic models and inequalities, and other related fields; further, they address e.g. average autoregression quantiles, neural networks, weighted empirical minimum distance estimators, implied volatility surface estimation, the Grenander estimator, non-Gaussian component analysis, meta learning, and high-dimensional errors-in-variables models.
650 0 $a Mathematical statistics $3 182294
650 1 4 $a Statistical Theory and Methods. $3 274054
650 2 4 $a Probability Theory and Stochastic Processes. $3 274061
650 2 4 $a Applications of Mathematics. $3 273744
650 2 4 $a Statistics and Computing/Statistics Programs. $3 275710
650 2 4 $a Applied Statistics. $3 805583
700 1 $a Maciak, Matus. $3 874469
700 1 $a Pesta, Michal. $3 874470
700 1 $a Schindler, Martin. $3 874471
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Springer proceedings in mathematics & statistics ; $v v.19. $3 569116
856 4 0 $u https://doi.org/10.1007/978-3-030-48814-7
950 $a Mathematics and Statistics (SpringerNature-11649)