Equivalence Between Out-of-Sample Forecast Comparisons and Wald Statistics∗
نویسندگان
چکیده
We demonstrate the equivalence between commonly used test statistics for out-of-sample forecasting performance and conventional Wald statistics. This equivalence greatly simplifies the computational burden of calculating recursive out-of-sample test statistics and their critical values. Moreover, for the case with nested models we show that the limit distribution, which has previously been expressed through stochastic integrals, has a simple representation in terms of χ-distributed random variables and we derive its density. We also generalize the limit theory to cover local alternatives and characterize the power properties of the test.
منابع مشابه
Stochastic and Dependence Comparisons Between Extreme Order Statistics in the Case of Proportional Reversed Hazard Model
Independent random variables $Y_{1},ldots ,Y_{n}$ belongs to the proportional reversed hazard rate (PRHR) model with proportionality parameters $lambda_1,...,lambda_n$, if $Y_{k}sim G^{lambda _{k}}(x)$, for $k=1,...,n$, where $G$ is an absolutely continuous distribution function. In this paper we compare the smallest order statistics, the sample ranges and th...
متن کاملNested Forecast Model Comparisons: A New Approach to Testing Equal Accuracy
This paper develops bootstrap methods for testing whether, in a finite sample, competing out-of-sample forecasts from nested models are equally accurate. Most prior work on forecast tests for nested models has focused on a null hypothesis of equal accuracy in population — basically, whether coefficients on the extra variables in the larger, nesting model are zero. We instead use an asymptotic a...
متن کاملON THE COMPATIBILITY OF A CRISP RELATION WITH A FUZZY EQUIVALENCE RELATION
In a recent paper, De Baets et al. have characterized the fuzzytolerance and fuzzy equivalence relations that a given strict order relation iscompatible with. In this paper, we generalize this characterization by consideringan arbitrary (crisp) relation instead of a strict order relation, while payingattention to the particular cases of a reflexive or irreflexive relation. The reasoninglargely ...
متن کاملRobust Forecast Comparison*
Forecast accuracy is typically measured in terms of a given loss function. However, as a consequence of the use of misspecified models in multiple model comparisons, relative forecast rankings are loss function dependent. This paper addresses this issue by using a novel criterion for forecast evaluation which is based on the entire distribution of forecast errors. We introduce the concepts of g...
متن کاملA note on sample size calculation for mean comparisons based on noncentral t-statistics.
One-sample and two-sample t-tests are commonly used in analyzing data from clinical trials in comparing mean responses from two drug products. During the planning stage of a clinical study, a crucial step is the sample size calculation, i.e., the determination of the number of subjects (patients) needed to achieve a desired power (e.g., 80%) for detecting a clinically meaningful difference in t...
متن کامل