We consider the class of graphs containing no odd hole, no odd antihole and no configuration consisting of three paths between two nodes such that any two of the paths induce a hole and at least two of the paths are of length 2. This class generalizes claw-free Berge graphs and square-free Berge...

I introduce the new mgof command to compute distributional tests for discrete (categorical, multinomial) variables. The command supports large-sample tests for complex survey designs and exact tests for small samples as well as classic large-sample Chi^2-approximation tests based on Pearson’s...

A new Stata command called -mgof- is introduced. The command is used to compute distributional tests for discrete (categorical, multinomial) variables. Apart from classic large sample $\chi^2$-approximation tests based on Pearson's $X^2$, the likelihood ratio, or any other statistic from the...

We consider the class of graphs containing no odd hole, no odd antihole and no configuration consisting of three paths between two nodes such that any two of the paths induce a hole and at least two of the paths are of length 2. This class generalizes claw-free Berge graphs and square-free Berge...

Given a dictionary of Mn initial estimates of the unknown true regression function, we aim to construct linearly aggregated estimators that target the best performance among all the linear combinations under a sparse q-norm (0 = q = 1) constraint on the linear coefficients. Besides identifying...

In most empirical studies, once the best model has been selected according to a certain criterion, subsequent analysis is conducted conditionally on the chosen model. In other words, the uncertainty of model selection is ignored once the best model has been chosen. However, the true...

Global vector autoregressions (GVARs) have several attractive features: multiple potential channels for the international transmission of macroeconomic and financial shocks, a standardized economically appealing choice of variables for each country or region examined, systematic treatment of...

This paper investigates whether and to what extent multiple encompassing tests may help determine weights for forecast averaging in a standard vector autoregressive setting. To this end we consider a new test-based procedure, which assigns non‐zero weights to candidate models that add...

We consider a diffusion process (X <Subscript> t </Subscript>)<Subscript> t ≥ 0</Subscript>, with drift b(x) and diffusion coefficient σ(x). At discrete times t <Subscript> k </Subscript> = k δ for k from 1 to M, we observe noisy data of the sample path, <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$${Y_{k\delta}=X_{k\delta}+\varepsilon_{k}}$$</EquationSource > </InlineEquation> . The random variables <InlineEquation ID="IEq2"> <EquationSource...</equationsource></inlineequation></equationsource></inlineequation></subscript></subscript></subscript>

Social scientists often consider multiple empirical models of the same process. When these models are parametric and non-nested, the null hypothesis that two models fit the data equally well is commonly tested using methods introduced by Vuong (Econometrica 57(2):307–333, <CitationRef CitationID="CR30">1989</CitationRef>) and Clarke (Am...</citationref>