搜索结果: 61-75 共查到“知识库 管理学 Time series”相关记录77条 . 查询时间(0.054 秒)
Sparse Causal Discovery in Multivariate Time Series
Vector Autoregressive Model Granger Causality Group Lasso Multiple Testing
2010/3/17
Our goal is to estimate causal interactions in multivariate time series.
Using vector autoregressive (VAR) models, these can be defined based on
non-vanishing coecients belonging to respective time...
A mathematical proof of the existence of trends in financial time series
Financial time series mathematical finance technical analysis trends random walks efficient markets
2010/3/17
We are settling a longstanding quarrel in quantitative finance by proving the
existence of trends in financial time series thanks to a theorem due to P. Cartier
and Y. Perrin, which is expressed in ...
Confidence bands in nonparametric time series regression
Long-range dependence model validation moderate deviation nonlinear time series nonparametric regression short-range dependence
2010/4/30
We consider nonparametric estimation of mean regression and
conditional variance (or volatility) functions in nonlinear stochastic
regression models. Simultaneous confidence bands are constructed
a...
Regularly varying multivariate time series
clusters of extremes extremal index heavy tails mixing moving average multivariate regular variation point processes
2010/4/30
A multivariate, stationary time series is said to be jointly regularly
varying if all its finite-dimensional distributions are multivariate regularly
varying. This property is shown to be equivalent...
SiZer for time series：A new approach to the analysis of trends
Autocovariance function estimation Local linearfit Scale-space method Sizer Time series
2010/4/29
Smoothing methods and SiZer are a useful statistical tool for
discovering statistically significant structure in data. Based on scale space
ideas originally developed in the computer vision literatu...
Nonparametric estimation for dependent data with an application to panel time series
Density estimation nonparametric regression 2-mixing,nonlinear processes panel time series
2010/4/29
In this paper we consider nonparametric estimation for dependent data, where the
observations do not necessarily come from a linear process. We study density estimation
and also discuss associated p...
Bootstrapping confidence intervals for the change-point of time series
confidence intervals block bootstrap mixing change in mean
2010/4/29
We study an AMOC time series model with an abrupt change in the mean and
dependent errors that fulfill certain mixing conditions. We obtain confidence intervals
for the unknown change-point via boot...
Linear Prediction of Long-Range Dependent Time Series
Long memory linear model autoregressive process forecast error
2010/4/26
We present two approaches for next step linear prediction of long memory time series. The
first is based on the truncation of the Wiener-Kolmogorov predictor by restricting the observations to the la...
Cowles commission structural equation approach in light of nonstationary time series analysis
Cowles commission structural equation approach nonstationary time series analysis
2010/4/27
We review the advancement of nonstationary time series analysis
from the perspective of Cowles Commission structural equation approach.
We argue that despite the rich repertoire nonstationary time s...
Combining domain knowledge and statistical models in time series analysis
time series analysis domain knowledge empirical models mechanisticmodels combined substantive-empirical approach basis function
2010/4/27
This paper describes a new approach to time series modeling that
combines subject-matter knowledge of the system dynamics with statistical
techniques in time series analysis and regression. Applicat...
Time series aggregation，disaggregation and long memory
random coefficient AR(1) long memory aggregation disaggregation
2010/4/27
The paper studies the aggregation/disaggregation problem
of random parameter AR(1) processes and its relation to the long memory
phenomenon. We give a characterization of a subclass of aggregated
p...
Modeling macroeconomic time series via heavy tailed distributions
seasonal adjustment outliers model selection t-distribution economictime series
2010/4/27
It has been shown that some macroeconomic time series, especially
those where outliers could be present, can be well modelled using heavy tailed
distributions for the noise components. Methods for d...
Conditional-sum-of-squares estimation of models for stationary time series with long memory
long memory conditional-sum-of-squares estimation central limit theorem almost sure convergence
2010/4/27
Employing recent results of Robinson (2005) we consider the asymptotic
properties of conditional-sum-of-squares (CSS) estimates of parametric
models for stationary time series with long memory. CSS ...
Quasi-maximum-likelihood estimation in conditionally heteroscedastic time series：A stochastic recurrence equations approach
Stochastic recurrence equation conditionally heteroscedastictime series GARCH asymmetric GARCH exponential GARCH EGARCH
2010/4/27
This paper studies the quasi-maximum-likelihood estimator
(QMLE) in a general conditionally heteroscedastic time series model
of multiplicative form Xt = tZt, where the unobservable volatility t
...
A comparison of statistical models for short categorical or ordinal time series with applications in ecology
time series categorical variable ordinal variable regression model Markov chain auto-regressive process estimation
2010/4/27
We study two statistical models for short-length categorical (or ordinal) time series. The first one is a regression
model based on generalized linear model. The second one is a parametrized Markovia...