共查询到20条相似文献,搜索用时 15 毫秒
1.
Earlier work has provided an efficient method for the prediction of missing data in a dependent variable series using a system of grouped regression equations. This paper extends the previous literature in two ways. First, a test statistic capable of indicating the advantage of the grouped procedure is derived. Second, it is demonstrated through an empirical application that the most prevalent methodology used for examining the impact of financial economic events is a special case of the missing data estimation problem. 相似文献
2.
Steve Beveridge 《统计学通讯:理论与方法》2013,42(12):3479-3496
The minimum mean square error linear interpolator for missing values in time series is extended to handle any pattern of nonconsecutive observations. The paper then develops evidence with simple ARMA models that the usefulness of either the"nonparametric"or the parametric form of the least squares interpolator depends on the time series model, the arrangement of the missing data and the objective for completing the series. 相似文献
3.
A linear recursive technique that does not use the Kalman filter approach is proposed to estimate missing observations in an univariate time series. It is assumed that the series follows an invertible ARIMA model. The procedure is based on the restricted forecasting approach, and the recursive linear estimators are optimal in terms of minimum mean-square error. 相似文献
4.
It is well known that if some observations in a sample from the probability density are not available, then in general the density cannot be estimated. A possible remedy is to use an auxiliary variable that explains the missing mechanism. For this setting a data-driven estimator is proposed that mimics performance of an oracle that knows all observations from the sample. It is also proved that the estimator adapts to unknown smoothness of the density and its mean integrated squared error converges with a minimax rate. A numerical study, together with the analysis of a real data, shows that the estimator is feasible for small samples. 相似文献
5.
We consider parameter estimation for time-dependent locally stationary long-memory processes. The asymptotic distribution of an estimator based on the local infinite autoregressive representation is derived, and asymptotic formulas for the mean squared error of the estimator, and the asymptotically optimal bandwidth are obtained. In spite of long memory, the optimal bandwidth turns out to be of the order n-1/5 and inversely proportional to the square of the second derivative of d. In this sense, local estimation of d is comparable to regression smoothing with iid residuals. 相似文献
6.
A doubly stochastic process {x(b,t);b?B,t?Z} is considered, with (B,β,Pβ) being a probability space so that for each b, {X(b,t);t ? Z} is a stationary process with an absolutely continuous spectral distribution. The population spectrum is defined as f(ω) = EB[Q(b,ω)] with Q(b,ω) being the spectral density function of X(b,t). The aim of this paper is to estimate f(ω) by means of a random sample b1,…,br from (B,β,Pβ). For each b1? B, the processes X(b1,t) are observed at the same times t=1,…,N. Thus, r time series (x(b1,t)} are available in order to estimate f(ω). A model for each individual periodogram, which involves f(ω), is formulated. It has been proven that a certain family of linear stationary processes follows the above model In this context, a kernel estimator is proposed in order to estimate f(ω). The bias, variance and asymptotic distribution of this estimator are investigated under certain conditions. 相似文献
7.
Han Lin Shang 《Statistics and Computing》2018,28(1):1-10
Bootstrap methods for estimating the long-run covariance of stationary functional time series are considered. We introduce a versatile bootstrap method that relies on functional principal component analysis, where principal component scores can be bootstrapped by maximum entropy. Two other bootstrap methods resample error functions, after the dependence structure being modeled linearly by a sieve method or nonlinearly by a functional kernel regression. Through a series of Monte-Carlo simulation, we evaluate and compare the finite-sample performances of these three bootstrap methods for estimating the long-run covariance in a functional time series. Using the intraday particulate matter (\(\hbox {PM}_{10}\)) dataset in Graz, the proposed bootstrap methods provide a way of constructing the distribution of estimated long-run covariance for functional time series. 相似文献
8.
In this paper, we investigate the asymptotic properties of a non-parametric conditional mode estimation given a functional explanatory variable, when functional stationary ergodic data and missing at random responses are observed. First of all, we establish asymptotic properties for a conditional density estimator from which we derive almost sure convergence (with rate) and asymptotic normality of a conditional mode estimator. This new estimate take into account missing data, and a simulation study is performed to illustrate how this fact allows to get higher predictive performances than those obtained with standard estimates. 相似文献
9.
This article considers the problem of testing for linearity of stationary time series. Portmanteau tests are discussed which are based on generalized correlations of residuals from a linear model (that is, autocorrelations and cross-correlations of different powers of the residuals). The finite-sample properties of the tests are assessed by means of Monte Carlo experiments. The tests are applied to 100 time series of stock returns. 相似文献
10.
José D. Bermúdez Ana Corberán-Vallet Enriqueta Vercher 《Journal of statistical planning and inference》2009
This paper deals with the prediction of time series with missing data using an alternative formulation for Holt's model with additive errors. This formulation simplifies both the calculus of maximum likelihood estimators of all the unknowns in the model and the calculus of point forecasts. In the presence of missing data, the EM algorithm is used to obtain maximum likelihood estimates and point forecasts. Based on this application we propose a leave-one-out algorithm for the data transformation selection problem which allows us to analyse Holt's model with multiplicative errors. Some numerical results show the performance of these procedures for obtaining robust forecasts. 相似文献
11.
Philip Byrne 《统计学通讯:理论与方法》2013,42(6):1935-1943
When a covariance matrix has a pattern associated with a stationary time series on the errors, it is shown how certain hypothesis testing problems In multivariate analysis can be transformed into a product of two similar multivariate problems that each involve unpatterned covariance matrices. 相似文献
12.
B. Abraham 《统计学通讯:理论与方法》2013,42(16):1643-1653
A method based on forecasting techniques is proposed to estimate missing observations in time series. Using mean squares, this method is compared to the minimum mean square estimate. 相似文献
13.
Xavier De Luna 《Journal of applied statistics》1998,25(6):763-775
Polynomial autoregressions are usually considered to be unrealistic models for time series. However, this paper shows that they can successfully be used when the purpose of the time series study is to provide forecasts. A projection scheme inspired from projection pursuit regression and feedforward artificial neural networks is used in order to avoid an explosion of the number of parameters when considering a large number of lags. The estimation of the parameters of the projected polynomial autoregressions is a non-linear least-squares problem. A consistency result is proved. A simulation study shows that the naive use of the common final prediction error criterion is inappropriate to identify the best projected polynomial autoregression. An explanation of this phenomenon is given and a correction to the criterion is proposed. An important feature of the polynomial predictors introduced in this paper is their simple implementation, which allows for automatic use. This is illustrated with real data for the three-month US Treasury Bill. 相似文献
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15.
Statistics and Computing - Long memory has been observed for time series across a multitude of fields, and the accurate estimation of such dependence, for example via the Hurst exponent, is crucial... 相似文献
16.
Lihong Wang 《统计学通讯:理论与方法》2019,48(10):2529-2547
The semiparametric estimators of time varying long memory parameter are investigated for locally stationary long memory processes. The GPH estimator and the local Whittle estimator are considered. Under some mild regularity assumptions, the weak consistency and the asymptotic normality of the estimators are obtained. The finite sample performance of the estimators is discussed through a small simulation study. 相似文献
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18.
The problem of classifying a covariance stationary normal time series is considered. Under certain regularity conditions, a compact form of the linear discriminant function in the sense of maximizing the Bhattacharyya distance is obtained. 相似文献
19.
《Journal of statistical planning and inference》2006,136(11):3904-3930
The problem of outlier estimation in time series is addressed. The least squares estimators of additive and innovation outliers in the framework of linear stationary and non-stationary models are considered and their bias is evaluated. As a result, simple alternative nearly unbiased estimators are proposed both for the additive and the innovation outlier types. A simulation study confirms the theoretical results and suggests that the proposed estimators are effective in reducing the bias also for short series. 相似文献