Titlebook: Nonparametric Statistics for Stochastic Processes; Estimation and Predi D. Bosq Book 1998Latest edition Springer Science+Business Media New

originality

Lecture Notes in Statisticshttp://image.papertrans.cn/n/image/667837.jpg

膝蓋

白楊

MAL

Synopsis,Classically time series analysis has two purposes.One of these is to construct a model which fits the data and then to estimate the model’s parameters. The second object is to use the identified model for prediction.

concise

Inequalities for mixing processes,In this chapter we present some inequalities for covariances, joint densities and partial sums of stochastic discrete time processes when dependence is measured by strong mixing coefficients. The main tool is coupling with independent random variables. Some limit theorems for mixing processes are given as applications.

曲解

Density estimation for discrete time processes,This chapter deals with nonparametric density estimation for sequences of correlated random variables.

松軟

Kernel density estimation for continuous time processes,In this chapter we investigate the problem of estimating density for continuous time processes when continuous or sampled data are available.

使困惑

Regression estimation and prediction in continuous time,Despite its great importance in practice, nonparametric regression estimation in continuous time has not been much studied up to now. The current chapter is perhaps the first general work on that topic.

deciduous

The local time density estimator,In this Chapter we use local time for constructing an unbiased estimator of density when continuous sample is available. This estimator appears to be natural since it is the density of empirical measure.

易發(fā)怒