排序方式: 共有16条查询结果,搜索用时 62 毫秒
1.
This paper analyses the large sample behaviour of a varying kernel density estimator of the marginal density of a non-negative stationary and ergodic time series that is also strongly mixing. In particular we obtain an approximation for bias, mean square error and establish asymptotic normality of this density estimator. We also derive an almost sure uniform consistency rate over bounded intervals of this estimator. A finite sample simulation shows some superiority of the proposed density estimator over the one based on a symmetric kernel. 相似文献
2.
The first-order product autoregressive (PAR(1)) model introduced by McKenzie in 1982 did not attract the attention of practitioners due to the unavailability of a proper estimation method. This article proposes an estimating function (EF) method to fill the gap. In particular, we suggest an optimal combination of linear and quadratic EFs to overcome the problem of parameter identification. The procedure is applied to Weibull and Gamma PAR(1) models. Simulation and data analysis show that the proposed method performs better than the existing methods. 相似文献
3.
Balakrishna Hosmane 《统计学通讯:理论与方法》2013,42(6):1725-1731
The purpose of this paper is to examine the asymptotic properties of the operational almost unbiased estimator of regression coefficients which includes almost unbiased ordinary ridge estimator a s a special case. The small distrubance approximations for the bias and mean square error matrix of the estimator are derived. As a consequence, it is proved that, under certain conditions, the estimator is more efficient than a general class of estimators given by Vinod and Ullah (1981). Also it is shown that, if the ordinary ridge estimator (ORE) dominates the ordinary least squares estimator then the almost unbiased ordinary ridge estimator does not dominate ORE under the mean square error criterion. 相似文献
4.
H. Pokhriyal N. Balakrishna 《Journal of Statistical Computation and Simulation》2019,89(15):2930-2950
In the recent past, the autoregressive conditional duration (ACD) models have gained popularity in modelling the durations between successive events. The aim of this paper is to propose a simple and distribution free re-sampling procedure for developing the forecast intervals of linear ACD Models. We use the conditional least squares method to estimate the parameters of the ACD Model instead of the conditional Maximum Likelihood Estimation or Quasi-Maximum Likelihood Estimation and show that they are consistent for large samples. The properties of the proposed procedure are illustrated by a simulation study and an application to two real data sets. 相似文献
5.
The average availability of a repairable system is the expected proportion of time that the system is operating in the interval [0, t]. The present article discusses the nonparametric estimation of the average availability when (i) the data on ‘n’ complete cycles of system operation are available, (ii) the data are subject to right censorship, and (iii) the process is observed upto a specified time ‘T’. In each case, a nonparametric confidence interval for the average availability is also constructed. Simulations are conducted to assess the performance of the estimators. 相似文献
6.
Some renewal theoretic properties of a renewal counting process induced by a Markov chain on the set of non-negative integers are established, namely, analogues of the classical elementary, Blackwell, and Breiman theorems and the key renewal theorem. These results generalize those of Vere-Jones (1975) who considered a Markov chain on the set of positive integers. 相似文献
7.
B.S. Hosmane 《统计学通讯:理论与方法》2013,42(6):1875-1888
When an I×J contingency table has many cells having very small frequencies, the usual chi-square approximation to the upper tail of the likelihood ratio goodness-of-fit statistic, G2 and Pearson chi-square statistic, X2, for testing independence, are not satisfactory. In this paper we consider the problem of adjusting G2 and X2. Suitable adjustments are suggested on the basis of analytical investigation of asymptotic bias terms for G2 and X2. A Monte Carlo simulation is performed for several tables to assess the adjustments of G2 and X2 in order to obtain a closer approximation to the nominal level of significance. 相似文献
8.
Under the assumption that the exponential distribution is a reasonable model for a given population, some shrinkage estimators for the location parameter based on type 1 and type II censored samples have been derived. It is shown that these estimators dominate maximum likelihood estimators (MLE's) asymptotically under the mean squared error (MSE) criterion. A Monte Carlo study shows a significant improvement of our estimators over MLE's in terms of MSE for small samples. 相似文献
9.
This article studies the problem of model identification and estimation for stable autoregressive process observed in a symmetric stable noise environment. A new tool called partial auto-covariation function is introduced to identify the stable autoregressive signals. The signal and noise parameters are estimated using a modified version of Generalized Yule Walker type method and the method of moments. The proposed methods are illustrated through data simulated from autoregressive signals with symmetric stable innovations. The new technique is applied to analyze the time series of sea surface temperature anomaly and compared with its Gaussian counterpart. 相似文献
10.
Balakrishna S. Hosmane 《统计学通讯:理论与方法》2013,42(6):1735-1740
This paper studies a generalized Stein estimator of regression coefficients. The small disturbance approximations for the bias and mean square error matrix of the estimator are derived and a necessary and sufficient condition is obtained for the estimator to dominate the ordinary least squares estimator under the mean square error criterion. 相似文献