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Works matching IS 0020-3157 AND VI 77 AND IP 1 AND DT 2025

Results: 6

1

Simplified quasi-likelihood analysis for a locally asymptotically quadratic random field: Simplified quasi-likelihood analysis: N. Yoshida.

Published in:

Annals of the Institute of Statistical Mathematics, 2025, v. 77, n. 1, p. 1, doi. 10.1007/s10463-024-00907-8

By:

Yoshida, Nakahiro

Publication type:

Article

2

Model free feature screening for large scale and ultrahigh dimensional survival data: Feature screening for large survival data: Y. Pan et al.

Published in:

Annals of the Institute of Statistical Mathematics, 2025, v. 77, n. 1, p. 155, doi. 10.1007/s10463-024-00912-x

By:

Pan, Yingli;
Wang, Haoyu;
Liu, Zhan

Publication type:

Article

3

Estimation of value-at-risk by Lp quantile regression: Estimation of VaR by Lp quantile regression: P. Sun et al.

Published in:

Annals of the Institute of Statistical Mathematics, 2025, v. 77, n. 1, p. 25, doi. 10.1007/s10463-024-00911-y

By:

Sun, Peng;
Lin, Fuming;
Xu, Haiyang;
Yu, Kaizhi

Publication type:

Article

4

Improved confidence intervals for nonlinear mixed-effects and nonparametric regression models: Improved CI for nonlinear mixed-effects models: N. Zheng, N. Cadigan.

Published in:

Annals of the Institute of Statistical Mathematics, 2025, v. 77, n. 1, p. 105, doi. 10.1007/s10463-024-00909-6

By:

Zheng, Nan;
Cadigan, Noel

Publication type:

Article

5

Hidden AR process and adaptive Kalman filter: Hidden AR process and adaptive Kalman filter: Y. A. Kutoyants.

Published in:

Annals of the Institute of Statistical Mathematics, 2025, v. 77, n. 1, p. 61, doi. 10.1007/s10463-024-00908-7

By:

Kutoyants, Yury A.

Publication type:

Article

6

Information projection approach to smoothed propensity score weighting for handling selection bias under missing at random: Information projection in missing data: H. Wang, J. K. Kim.

Published in:

Annals of the Institute of Statistical Mathematics, 2025, v. 77, n. 1, p. 127, doi. 10.1007/s10463-024-00913-w

By:

Wang, Hengfang;
Kim, Jae Kwang

Publication type:

Article