搜索结果: 1-15 共查到“数理统计学 time”相关记录36条 . 查询时间(0.244 秒)
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars:Estimating Time-Varying Networks for High-Dimensional Time Series
高维 时间序列 时变网络
2023/4/25
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars:Policy Choice in Time Series by Empirical Welfare Maximization
经验福利 最大化 时间序列 政策选择
2023/4/25
中山大学岭南学院高级计量经济学课件(II:Time series)Ch6 Cointegration
中山大学岭南学院 高级计量经济学 课件(II:Time series) Ch6 Cointegration
2017/6/14
中山大学岭南学院高级计量经济学课件(II:Time series)Ch6 Cointegration。
中山大学岭南学院高级计量经济学课件(II:Time series)CH5 Vector Autoregression (VAR) Models
中山大学岭南学院 高级计量经济学 课件(II:Time series) CH5 Vector Autoregression (VAR) Models
2017/6/14
中山大学岭南学院高级计量经济学课件(II:Time series)CH5 Vector Autoregression (VAR) Models。
中山大学岭南学院高级计量经济学课件(II:Time series)CH4 Unstationary Autoregressive Process
中山大学岭南学院 高级计量经济学 课件(II:Time series) CH4 Unstationary Autoregressive Process
2017/6/14
中山大学岭南学院高级计量经济学课件(II:Time series)CH4 Unstationary Autoregressive Process。
中山大学岭南学院高级计量经济学课件(II:Time series)CH3 ARCH and GARCH
中山大学岭南学院 高级计量经济学 课件(II:Time series) CH3 ARCH and GARCH
2017/6/14
中山大学岭南学院高级计量经济学课件(II:Time series)CH3 ARCH and GARCH。
中山大学岭南学院高级计量经济学课件(II:Time series)CH2 Stationary Autoregressive Process
中山大学岭南学院 高级计量经济学 课件(II:Time series) CH2 Stationary Autoregressive Process
2017/6/14
中山大学岭南学院高级计量经济学课件(II:Time series)CH2 Stationary Autoregressive Process。
中山大学岭南学院高级计量经济学课件(II:Time series)CH1 Basic Regression with Time Series
中山大学岭南学院 高级计量经济学 课件(II:Time series) CH1 Basic Regression with Time Series
2017/6/14
中山大学岭南学院高级计量经济学课件(II:Time series)CH1 Basic Regression with Time Series。
Second-order continuous-time non-stationary Gaussian autoregression
Lyapunov Exponent Maximum Likelihood Estimation Asymptotic Mixed Normality Non-Normal Limit Distribution Rate of Convergence
2012/6/27
The objective of the paper is to identify and investigate all possible types of asymptotic behavior for the maximum likelihood estimators of the unknown parameters in the second-order linear stochasti...
Factor modeling for high-dimensional time series: Inference for the number of factors
Autocovariance matrices blessing of dimensionality eigenanalysis fast convergence rates multivariate time series
2012/6/19
This paper deals with the factor modeling for high-dimensional time series based on a dimension-reduction viewpoint. Under stationary settings, the inference is simple in the sense that both the numbe...
SEMIPARAMETRIC DENSITY ESTIMATION FOR TIME SERIES WITH
semiparametric density estimation time series multiplicative adjustment
2011/11/11
In this paper, we extend a class of semiparametric density estimators to time series context. The asymptotic theory and simulation study are discussed. Theoretical results and numerical comparison sho...
Estimating Extremal Dependence in Univariate and Multivariate Time Series via the Extremogram
Extremogram extremal dependence stationary bootstrap financial time series
2011/10/9
Abstract: Davis and Mikosch [7] introduced the extremogram as a flexible quantitative tool for measuring various types of extremal dependence in a stationary time series. There we showed some standard...
High-frequency sampling and kernel estimation for continuous-time moving average processes
CARMA process continuous-time moving average process discretely sampled process FICARMA process gamma kernel
2011/9/19
Abstract: Interest in continuous-time processes has increased rapidly in recent years, largely because of the high-frequency data available in many areas of application, particularly in finance and tu...
Uniform hypothesis testing for ergodic time series distributions
Uniform hypothesis ergodic time series distributions Statistics Theory
2011/9/16
Abstract: Given a discrete-valued sample $X_1,...,X_n$ we wish to decide whether it was generated by a distribution belonging to a family $H_0$, or it was generated by a distribution belonging to a fa...
Scaling properties of first-passage time probabilities in financial markets
financial markets first-passage time probability Statistical Finance
2011/9/29
Abstract: Financial markets provide an ideal frame for the study of first-passage time events of non-Gaussian correlated dynamics mainly because large data sets are available. Tick-by-tick data of six...