Previous Page  9 / 12 Next Page
Information
Show Menu
Previous Page 9 / 12 Next Page
Page Background

В.Б. Горяинов, Е.Р. Горяинова

12

ISSN 1812-3368. Вестник МГТУ им. Н.Э. Баумана. Сер. Естественные науки. 2016. № 6

рию, основанному на выборочном коэффициенте ковариации. Определены зна-

чения асимптотической относительной эффективности для нормального рас-

пределения, двойного экспоненциального распределения (распределения

Лапласа) и загрязненного нормального распределения (распределения Тьюки).

ЛИТЕРАТУРА

1.

Schelter B., Winterhalder M., Timmer J.

Handbook of time series analysis: recent theoretical

developments and applications. Weinheim: Wiley, 2006. 508 p.

2.

Montgomery D.C., Jennings C.L., Kulahci M.

Introduction to time series analysis

and forecasting. Hoboken: Wiley, 2015. 655 p.

3.

Tsay R.S.

Analysis of time series. Hoboken: Wiley, 2010. 667 p.

4.

Rao T.S., Rao S.S., Rao C.R.

Handbook of statistics. Vol. 30. Time series analysis: methods

and applications. Amsterdam: Elsevier, 2012. 755 p.

5.

Wilson G.T., Reale M., Haywood J.

Models for dependent time series. Boca Raton:

CRC Press, 2015. 334 p.

6.

Daraio C., Simar L.

Advanced robust and nonparametric methods in efficiency analysis.

New York: Springer, 2007. 260 p.

7.

Huber P., Ronchetti E.M.

Robust statistics. Hoboken: Wiley, 2009. 360 p.

8.

Hettmansperger T.P., McKean J.W.

Robust nonparametric statistical methods. Boca Raton:

CRC Press, 2011. 535 p.

9.

Wilcox R.R.

Introduction to robust estimation and hypothesis testing. Amsterdam: Elsevier,

2012. 689 p.

10.

Andrews B.

Rank-based estimation for autoregressive moving average time series models //

J. Time Ser. Anal. 2008. Vol. 29. No. 1. P. 51–73.

11.

Goryainov V.B.

Identification of a spatial autoregression by rank methods // Automation

and Remote Control. 2011. Vol. 72. No. 5. P. 975–988.

12.

Goryainov V.B.

Least-modules estimates for spatial autoregression coefficients // Journal

of Computer and Systems Sciences International. 2011. Vol. 50. No. 4. P. 565–572.

13.

Горяинова Е.Р., Горяинов В.Б.

Знаковые критерии в модели скользящего среднего //

Вестник МГТУ им. Н.Э. Баумана. Сер. Естественные науки. 2008. № 1. С. 76–86.

14.

Goryainov V.B., Goryainova E.R.

Nonparametric identification of the spatial auto-

regression model under a priori stochastic uncertainty // Automation and Remote Control.

2010. No. 2. P. 198–208.

15.

Truquet L., Yao J.

On the quasi-likelihood estimation for random coefficient auto-

regressions // Statistics. 2012. Vol. 46. No. 4. P. 505–521.

16.

McLeod A.I.

On the distribution and applications of residual autocorrelations in Box-

Jenkins models // J. R. Statist. Soc. B. 1978. Vol. 40. P. 296–302.

17.

Hallin M., Puri M.L.

Optimal rank-based procedures for time series analysis: Testing

an ARMA model against other ARMA models // The Annals of Statistics. 1988. Vol. 16.

P. 402–432.

18.

Maronna R.A., Martin D., Yohai V.

Robust statistics: Theory and methods. Chichester:

Wiley, 2006. 403 p.