Các bài viết có thể truy cập công khai - Ling ShiqingTìm hiểu thêm
Không có ở bất kỳ nơi nào: 16
Asymptotic inference for AR models with heavy-tailed G-GARCH noises
R Zhang, S Ling
Econometric Theory 31 (4), 880-890, 2015
Các cơ quan ủy nhiệm: National Natural Science Foundation of China, Research Grants Council, Hong Kong
Testing for structural change of predictive regression model to threshold predictive regression model
F Zhu, M Liu, S Ling, Z Cai
Journal of Business & Economic Statistics 41 (1), 228-240, 2022
Các cơ quan ủy nhiệm: Australian Research Council, National Natural Science Foundation of China …
Self-weighted LAD-based inference for heavy-tailed threshold autoregressive models
Y Yang, S Ling
Journal of Econometrics 197 (2), 368-381, 2017
Các cơ quan ủy nhiệm: Research Grants Council, Hong Kong
Inference in heavy-tailed vector error correction models
R She, S Ling
Journal of Econometrics 214 (2), 433-450, 2020
Các cơ quan ủy nhiệm: Australian Research Council, National Natural Science Foundation of China …
Whittle parameter estimation for vector ARMA models with heavy-tailed noises
R She, Z Mi, S Ling
Journal of Statistical Planning and Inference 219, 216-230, 2022
Các cơ quan ủy nhiệm: Australian Research Council, National Natural Science Foundation of China …
Testing serial correlation and ARCH effect of high-dimensional time-series data
S Ling, RS Tsay, Y Yang
Journal of Business & Economic Statistics 39 (1), 136-147, 2021
Các cơ quan ủy nhiệm: Australian Research Council, National Natural Science Foundation of China …
Inference for heavy-tailed and multiple-threshold double autoregressive models
Y Yang, S Ling
Journal of Business & Economic Statistics 35 (2), 318-333, 2017
Các cơ quan ủy nhiệm: Research Grants Council, Hong Kong
LADE-based inferences for autoregressive models with heavy-tailed G-GARCH (1, 1) noise
X Zhang, R Zhang, Y Li, S Ling
Journal of Econometrics 227 (1), 228-240, 2022
Các cơ quan ủy nhiệm: Australian Research Council, National Natural Science Foundation of China …
Diagnostic checking for non-stationary ARMA models with an application to financial data
S Ling, K Zhu, CC Yee
The North American Journal of Economics and Finance 26, 624-639, 2013
Các cơ quan ủy nhiệm: Research Grants Council, Hong Kong
Quasi-likelihood estimation of structure-changed threshold double autoregressive models
F Guo, S Ling
Journal of Statistical Planning and Inference 205, 138-155, 2020
Các cơ quan ủy nhiệm: Australian Research Council, National Natural Science Foundation of China …
Goodness-of-fit test for nonlinear time series models
NS Han, S Ling
Annals of Financial Economics 12 (02), 1750006, 2017
Các cơ quan ủy nhiệm: Research Grants Council, Hong Kong
Asymptotic inference of the ARMA model with time‐functional variance noises
B Cai, E Zhu, S Ling
Scandinavian Journal of Statistics 51 (3), 1230-1258, 2024
Các cơ quan ủy nhiệm: Research Grants Council, Hong Kong
Inference for the VEC (1) model with a heavy-tailed linear process errors
F Guo, S Ling
Econometric Reviews 42 (9-10), 806-833, 2023
Các cơ quan ủy nhiệm: Australian Research Council, Research Grants Council, Hong Kong
Consistency of global LSE for MA (1) models
Y Yang, S Ling, Q Wang
Statistics & Probability Letters 182, 109292, 2022
Các cơ quan ủy nhiệm: Australian Research Council, National Natural Science Foundation of China …
On ergodicity of threshold ARMA(m, p, q) models
Q Bai, S Ling
Japanese Journal of Statistics and Data Science, 1-9, 2024
Các cơ quan ủy nhiệm: Research Grants Council, Hong Kong
A note on the LSE of three-regime TAR model with an infinite variance
Y Yang, S Ling
Annals of Financial Economics 13 (02), 1850007, 2018
Các cơ quan ủy nhiệm: Research Grants Council, Hong Kong
Có tại một số nơi: 20
Estimation in nonstationary random coefficient autoregressive models
I Berkes, L Horváth, S Ling
Journal of Time Series Analysis 30 (4), 395-416, 2009
Các cơ quan ủy nhiệm: Hungarian Scientific Research Fund
The ZD-GARCH model: A new way to study heteroscedasticity
D Li, X Zhang, K Zhu, S Ling
Journal of Econometrics 202 (1), 1-17, 2018
Các cơ quan ủy nhiệm: Chinese Academy of Sciences, National Natural Science Foundation of China …
On a threshold double autoregressive model
D Li, S Ling, R Zhang
Journal of Business & Economic Statistics 34 (1), 68-80, 2016
Các cơ quan ủy nhiệm: National Natural Science Foundation of China, Research Grants Council, Hong Kong
LADE-based inference for ARMA models with unspecified and heavy-tailed heteroscedastic noises
K Zhu, S Ling
Journal of the American Statistical Association 110 (510), 784-794, 2015
Các cơ quan ủy nhiệm: Chinese Academy of Sciences, National Natural Science Foundation of China …
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