AR(2) estimator
On comparison some estimators in small area study
... James-Stein estimator, ...proportion estimator, 2.85182, and next one, previous year batting average estimator, ...James-Stein estimator is even better than summarize overall past experiences ...
6
Quasi maximum exponential likelihood estimator and portmanteau test of double \(\operatorname{AR}(p)\) model based on \(\operatorname{Laplace}(a,b)\)
... double AR(p) as an extension of the ARCH ...double AR(p) model is an AR(p) model with conditional ...double AR(1) model under weak conditions, finally presented an empirical ...double ...
11
Some Improvement on Convergence Rates of Kernel Density Estimator
... Without loss of generality, we suppose f is the standard normal density. We randomly select 1000 indepen- dent samples of size n = 20, 50, 100 or 200. We choose arbitrarily the points x = 0, 0.5, 1, 1.5, 2, 2.5 ...
13
Inferring the behavior of distributed energy resources from incomplete measurements (project outputs)
... We conduct a series of case studies, varying: 1) the average delay, 2) the reference signal, 3) the model used to simulate individual TCLs within the plant, and 4) the estimator. The two reference signals, ...
11
Estimating and Predicting Value at Risk in Selected Banks of Nigeria Stock Market
... 1;0.01 2 = 6.635 . Also, it is expected that if the estimator is well specified that the failure rate should be the same or at worse very close to the value 𝛼𝛼 ...the estimator is ...Gaussian ...
5
On the distribution of the adaptive LASSO estimator
... LASSO estimator are introduced in Section ...the estimator theoretically in an orthogonal linear regression ...LASSO estimator are discussed in Section ...the estimator are the subject of ...
26
Estimator selection
... Unbiased criteria, such as corrected V -fold cross-validation, are obtained for C = 1, i.e. δ = 0. Theorem 2 shows they are asymptotically optimal. More generally, δ measures the bias of the V -fold penalization ...
14
ESTIMATORS OF LINEAR REGRESSION MODEL WITH AUTOCORRELATED ERRROR TERMS AND PREDICTION USING CORRELATED UNIFORM REGRESSORS
... These figures reveal that the performances of COR and ML estimators at each level of multicollinearity over the levels of autocorrelation are convex – like while that of the OLS and PC estimators are concave. Also, as ...
10
A plug in averaging estimator for regressions with heteroskedastic errors
... Empirical studies often must consider whether additional regressors should be included in the baseline model. Adding more regressors reduces the model bias but causes a large variance. To address the trade-off between ...
46
Isotonic Change Point Estimation in the AR(1) Autocorrelated Simple Linear Profiles
... in which log e L ( ) ˆ is the maximum of the log likelihood function achieved over all possible change points t. As seen in Equation (18) , if the value of the log likelihood function at time t i.e. log e L t ( ) ...
9
Nonparametric circular quantile regression
... Firstly we note that, as expected, estimator (5) is a little better than (10) in all settings. However, the improvement comes at a computational price. The first set of results shows a similar performance for each ...
16
Performance of Existing Biased Estimators and the Respective Predictors in a Misspecified Linear Regression Model
... DOI: 10.4236/ojs.2017.75062 878 Open Journal of Statistics The rest of this article is organized as follows. The model specification and respective OLSE are written in section 2. In section 3, generalized form to ...
25
Review of some ratio estimators in stratified random sampling
... rational estimator, which is one of these estimators, Kadılar-Çıngı 1 ratio estimator, which is obtained through adaptation of the estimator, which is suggested by Sisodia-Dwidedi (1981) in simple ...
11
A Novel Parameter Estimation Method Based on LSU-EKF for Polynomial Phase Signal
... LSU estimator [18], the HAF estimator [16], the PHAF estimator [17], the Zhou and Wang (ZW) estimator [36] are compared with the proposed LSU-EKF estimator under the same experimental ...
14
Estimating a Bounded Normal Mean Under the LINEX Loss Function
... another estimator and compared the risk performance of it with the above- mentioned ...dominating estimator, derived inadmissibility of MLE of the mean ...
8
Sample Spaced and Fractionally Spaced CIR Estimation Aided Decision Directed Channel Estimation for OFDM and MC CDMA
... FS-CIR estimator outperforms its SS-CIR estimator-based counter- ...FS-CIR estimator-based method exhibits higher robustness to various channel parameters such as the channel’s root mean square delay ...
5
MoL 2004 02: A Consistent and Efficient Estimator for the Data Oriented Parsing Model
... • The estimator, although not truly maximum likelihood, is consistent. The assumption also serves a principle of simplicity: A shorter derivation seems a more concise description of a full parse tree than a longer ...
69
Estimators of Linear Regression Model and Prediction under Some Assumptions Violation
... diction of its values often becomes very essential and necessary. Moreover, the linear regression model is for- mulated under some basic assumptions. Among these as- sumptions are regressors being assumed to be non-sto- ...
13
Empirical likelihood based inference in Poisson autoregressive model with conditional moment restrictions
... The EL as an alternative to the bootstrap for constructing confidence regions was intro- duced by Owen [, ]. The method defines an EL ratio function to construct confidence regions. Important features of the empirical ...
13
Estimating a Bounded Normal Mean Relative to Squared Error Loss Function
... another estimator and compared the risk performance of it with the above- mentioned ...dominating estimator, derived inadmissibility of MLE of the mean ...
10