Zobrazeno 1 - 10
of 7 676
pro vyhledávání: '"Statistics::Applications"'
Autor:
Guan, Qian, Yang, Shu
Publikováno v:
Statistica Sinica.
Multiple imputation is widely used to handle missing data. Although Rubin's combining rule is simple, it is not clear whether or not the standard multiple imputation inference is consistent when coupled with the commonly-used full sample estimators.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b766991e09f34ac2991fe2ea560ffe8f
https://doi.org/10.5705/ss.202021.0404
https://doi.org/10.5705/ss.202021.0404
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 35:2837-2846
Missing data widely exist in the raw or processed data, implying information loss. In many cases, missing values have to be accurately imputed for further use. In this paper, an extreme case, consecutively missing data in large-length and mainly rema
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::82b604dee5e8ef19029c5913f3d73f5d
https://doi.org/10.1109/tkde.2021.3109115
https://doi.org/10.1109/tkde.2021.3109115
Publikováno v:
Journal of Econometrics. 230:453-482
This paper considers the inference problems in nonlinear quantile regressions with both stationary and nonstationary covariates. The nonparametric local constant quantile estimator is proposed to estimate the unknown quantile regression function, who
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9bb12868bd20fe7e1e7a95528d81cabc
https://doi.org/10.1016/j.jeconom.2021.06.002
https://doi.org/10.1016/j.jeconom.2021.06.002
Autor:
Xun Pang, Licheng Liu
Publikováno v:
Political Science Research and Methods. :1-15
This paper proposes a Bayesian multifactor spatio-temporal model with a dynamic spatial autoregressive coefficient to estimate time-varying network interdependence with time-series cross-sectional data. To correct biases caused by unobserved time-var
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d2df97a3068bf0b2be385978834fc00a
https://doi.org/10.1017/psrm.2022.47
https://doi.org/10.1017/psrm.2022.47
Publikováno v:
Econometrics and Statistics. 23:36-52
Diurnal fluctuations in volatility are a well-documented stylized fact of intraday price data. This warrants an investigation how this intraday periodicity (IP) affects both finite sample as well as asymptotic properties of several popular realized e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::77595e8a2cc2aed82b5ee09c16785d23
https://doi.org/10.1016/j.ecosta.2021.03.002
https://doi.org/10.1016/j.ecosta.2021.03.002
Publikováno v:
Communications in Statistics - Simulation and Computation. :1-17
Data sets with missing values bring great challenges to k-means clustering (KMC). At present, most studies focus on KMC data with low missing ratio while few studies on KMC data with high missing ratio. The current imputation methods have the followi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::942a7919571c225467c591ee851d38b9
https://doi.org/10.1080/03610918.2022.2091779
https://doi.org/10.1080/03610918.2022.2091779
Autor:
Wang, Hengfang, Kim, Jae Kwang
Publikováno v:
Annals of the Institute of Statistical Mathematics.
Imputation and propensity score weighting are two popular techniques for handling missing data. We address these problems using the regularized M-estimation techniques in the reproducing kernel Hilbert space. Specifically, we first use the kernel rid
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e980e1e2b4d4f6c6a280a469b844973f
https://doi.org/10.1007/s10463-023-00872-8
https://doi.org/10.1007/s10463-023-00872-8
Publikováno v:
Sustainable Business and Society in Emerging Economies. 4:25-32
Purpose: The purpose of this study is to specify an efficient forecast model for the accurate prediction of macroeconomic variables in the context of Pakistan. Design/Methodology/Approach: We particularly investigate the comparative accuracy of Artif
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::84301d114d638371bc980dce04be0b00
https://doi.org/10.26710/sbsee.v4i1.2147
https://doi.org/10.26710/sbsee.v4i1.2147
Publikováno v:
Stats; Volume 5; Issue 2; Pages: 358-370
Missing covariate values are a common problem in survival studies, and the method of choice when handling such incomplete data is often multiple imputation. However, it is not obvious how this can be used most effectively when an incomplete covariate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2f861a608b757949391013bd03ac673c
https://doi.org/10.3390/stats5020020
https://doi.org/10.3390/stats5020020
Autor:
Samuel Asante Gyamerah
Publikováno v:
Journal of King Saud University - Computer and Information Sciences. 34:1003-1009
High frequency Bitcoin price series are often non-linear and non-stationary and hence forecasting the price of Bitcoin directly or by transformation using statistical models is subject to large errors. This paper presents an ensemble model using vari
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b51dfd56051eac4f39e4849010c91661
https://doi.org/10.1016/j.jksuci.2020.01.006
https://doi.org/10.1016/j.jksuci.2020.01.006