A Single-Sample Estimate of Shrinkage in Meteorological Forecasting
نویسندگان
چکیده
An estimator of shrinkage based on information contained in a single sample is presented and the results of a simulation study are reported. The effects of sample size, amount, and severity of nonrepresentative data in the population, inclusion of noninformative predictors, and least (sum of ) absolute deviations and least (sum of ) squared deviations regression models are examined on the estimator. A single-sample estimator of shrinkage based on drop-one cross-validation is shown to be highly accurate under a wide variety of research conditions.
منابع مشابه
Beyond Optimal Forecasting
While the conditional mean is known to provide the minimum mean square error (MSE) forecast – and hence is optimal under a squared-error loss function – it must often in practice be replaced by a noisy estimate when model parameters are estimated over a small sample. Here two results are obtained, both of which motivate the use of forecasts biased toward zero (shrinkage forecasts) in such setti...
متن کاملForecasting Crude Oil prices Volatility and Value at Risk: Single and Switching Regime GARCH Models
Forecasting crude oil price volatility is an important issues in risk management. The historical course of oil price volatility indicates the existence of a cluster pattern. Therefore, GARCH models are used to model and more accurately predict oil price fluctuations. The purpose of this study is to identify the best GARCH model with the best performance in different time horizons. To achieve th...
متن کاملIn-Sample and Out-of-Sample Fit: Their Joint Distribution and its Implications for Model Selection and Model Averaging (Criteria-Based Shrinkage for Forecasting)
We consider the case where a parameter, ; is estimated by maximizing a criterion function, Q(X ; ). The estimate is then used to evaluate the criterion function with the same data, X , as well as with an independent data set, Y. The in-sample t and out-of-sample t relative to that of 0; the trueparameter, are given by Tx;x = Q(X ; ̂x) Q(X ; 0) and Ty;x = Q(Y; ̂x) Q(Y; 0). We derive the limi...
متن کاملForecasting Natural Gas Demand Using Meteorological Data: Neural Network Method
The need for prediction and patterns of gas consumption especially in the cold seasons is essential for consumption management and policy planning decision making. In residential and commercial uses which account for the bulk of gas consumption in the country the effects of meteorological variables have the highest impact on consumption. In the present research four variables include daily ave...
متن کاملEvaluation of meteorological, hydrological and groundwater resources indicators for drought monitoring and forecasting in a semi-arid climate
Drought as a natural phenomenon characterized by a significant decrease of water availability during a period of time and over a large area. In recent years, droughts and its frequent in arid and semi-arid regions like Iran on the one hand, and water demand has been rising on the other hand and, as a result, their impacts are being aggravated. Therefore, the meteorological and hydrological...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 1997