Parameter estimators are derived for the nonlinear regression model under various assumptions. The limiting behavior of the estimators is investigated.doi:10.1007/BF01092334E. I. ZhilinskayaKluwer Academic Publishers-Plenum PublishersJournal of Mathematical Sciences
When the predictor and instrumental variables are normally distributed, we also propose a maximum likelihood based estimator and a two-stage moment estimator. Simulation studies show that all proposed estimators perform satisfactorily for relatively small samples and relatively high degree of censoring. In...
This paper deals with a nonlinear errors-in-variables model where the distributions of the unobserved predictor variables and of the measurement errors are nonparametric. Using theinstrumental variableapproach, we propose method of moments estimators for the unknown parameters and simulation-based estimators...
To include a constant in the differenced model, specify include.drift=TRUE.The auto.arima() function will also handle regression terms via the xreg argument. The user must specify the predictor variables to include, but auto.arima() will select the best ARIMA model for the errors. If ...
Uniform confidence bands for nonparametric errors-in-variables regression This paper develops a method to construct uniform confidence bands for a nonparametric regression function where a predictor variable is subject to a measu... K Kato,Y Sasaki 被引量: 7发表: 2017年 The persistent, spectral var...
Adjustable parameters depend on the modelType. In general, adjustable parameters include: Predictor variables for the linear regression component, listed in thePredictorssection. For regression models with ARMA errors, you must include at least one predictor in the model. To include a predictor, selec...
PresamplePredictorVariables="CPIDel",InSample=DTTFS, ... PredictorVariables="CPIDel") Tbl=8×7 timetable Time Interval GDP GDPRate CPIDel GDPRate_Response GDPRate_MSE GDPRate_RegressionInnovation ___ ___ ___ ___ ___ ___ ___ ___ Q2-07 91 0.00018278 0.018278 1.675 0.015765 0.00011319...
Predictor VariablesRegression (StatisticsHierarchical regression analysis is potentially a very useful statistical technique for establishing the significance of sets of predictor variables. However, when a hierarchical analysis which is based on theory is performed, some estimation procedures for the ...
InSample=DTT(frstHzn,:),PredictorVariables="CPIDel"); Plot the simulation median forecast and approximate 95% forecast intervals. TblSim.FStats = quantile(TblSim.GDPRate_Response,[0.025 0.5 0.975],2); figure plot(DTT.Time(end-40:end),DTT.GDPRate(end-40:end),Color=[.7,.7,.7]) ho...
By default,inferexcludes the regression component, regardless of its presence inMdl. Example:PredictorVariables=["M1SL" "TB3MS" "UNRATE"] Example:PredictorVariables=[true false true false]orPredictorVariable=[1 3]selects the first and third table variables to supply the predictor data. ...