搜索结果: 1-15 共查到“统计学 time series”相关记录73条 . 查询时间(0.125 秒)
IMPROVED SEMI-PARAMETRIC TIME SERIES MODELS OF AIR POLLUTION AND MORTALITY
Semiparametric regression time series Particulate Matter (PM) Generalized Additive Model Generalized Linear Model Mean Squared Error Bandwidth Selection
2015/8/21
In 2002, methodological issues around time series analyses of air pollution and health attracted the attention of the scientific community, policy makers, the press, and the diverse stakeholders conce...
Topics in Multivariate Time Series Analysis: Statistical Control, Dimension Reduction Visualization and Thir Business Applications
Topics in Multivariate Time Series Analysis Statistical Control Dimension Reduction Visualization Their Business Applications
2014/10/28
Most business processes are, by nature, multivariate and autocorrelated. Highdimensionality is rooted in processes where more than one variable is considered simultaneously to provide a more comprehen...
Dynamic Covariance Models for Multivariate Financial Time Series
Dynamic Covariance Models Multivariate Financial Time Series
2013/6/14
The accurate prediction of time-changing covariances is an important problem in the modeling of multivariate financial data. However, some of the most popular models suffer from a) overfitting problem...
Fourier analysis of stationary time series in function space
Cumulants discrete Fourier transform functional data analy-sis functional time series periodogram operator spectral density operator weak depen-dence
2013/6/14
We develop the basic building blocks of a frequency domain framework for drawing statistical inferences on the second-order structure of a stationary sequence of functional data. The key element in su...
Inference and testing for structural change in time series of counts model
time series of counts Poisson autoregression likelihood estimation change-point semi-parametric test
2013/6/14
We consider here together the inference questions and the change-point problem in Poisson autoregressions (see Tj{\o}stheim, 2012). The conditional mean (or intensity) of the process is involved as a ...
Approximate Inference for Observation Driven Time Series Models with Intractable Likelihoods
Observation Driven Time Series Models Approximate Bayesian Computation Asymptotic Con-sistency Markov Chain Monte Carlo
2013/4/28
In the following article we consider approximate Bayesian parameter inference for observation driven time series models. Such statistical models appear in a wide variety of applications, including eco...
A Robust Bayesian Dynamic Linear Model to Detect Abrupt Changes in an Economic Time Series: The Case of Puerto Rico
Dynamic Models Consumer Price Index Bayesian Robustness
2013/4/28
Economic indicators time series are usually complex with high frequency data. The traditional time series methodology requires at least a preliminary transformation of the data to get stationarity. On...
Asymptotic Normality of Estimates in Flexible Seasonal Time Series Model with Weak Dependent Error Terms
seasonal time series model local linear estimates consistency and asymptotic
2013/5/2
In this paper we considered a general seasonal time series model with K-dependent and \rambda-dependent errors, which are new concepts of dependence. In this model we derived consistency and asymptoti...
Environmental Time Series Interpolation Based on Spartan Random Processes
inference precision matrix gappy data atmospheric aerosol fine particulate PM2.5
2013/4/27
In many environmental applications, time series are either incomplete or irregularly spaced. We investigate the application of the Spartan random process to missing data prediction. We employ a novel ...
This paper is a note on the use of Bayesian nonparametric mixture models for continuous time series. We identify a key requirement for such models, and then establish that there is a single type of mo...
Inter Time Series Sales Forecasting
Association mining Combining Decomposition Forecasting Inter time series.
2013/4/27
Combining forecast from different models has shown to perform better than single forecast in most time series. To improve the quality of forecast we can go for combining forecast. We study the effect ...
Monitoring procedure for parameter change in causal time series
Sequential change detection Change-point Causal processes Quasi-maximum likelihood estimator Weak convergence.
2012/11/22
We propose a new sequential procedure to detect change in the parameters of a process $ X= (X_t)_{t\in \Z}$ belonging to a large class of causal models (such as AR($\infty$), ARCH($\infty$), TARCH($\i...
Diagnostic Tests for Non-causal Time Series with Infinite Variance
Non-causal AR Process Infinite Variance Goodness-of-fit Portmanteau Test alpha-stabledistribution
2012/11/22
We study goodness-of-fit testing for non-causal autoregressive time series with non-Gaussian stable noise. To model time series exhibiting sharp spikes or occasional bursts of outlying observations, t...
ARMA Time-Series Modeling with Graphical Models
ARMA Time-Series Modeling Graphical Models
2012/9/19
We express the classic ARMA time-series model as a directed graphical model. In doing so, we find that the deterministic re-lationships in the model make it effectively impossible to use the EM algori...
Interest Rate Manipulation Detection using Time Series Clustering Approach
Interest Rate Manipulation Detection Time Series Clustering Approach
2012/9/18
The Interbank Offered Rate is a vital benchmark interest rate in the financial markets of every country to which financial contracts are tied. In the light of the recent LIBOR manipulation incident, t...