We analyze multivariate binary time series using a mixed parameterization in terms of the conditional expectations given the past and the pairwise canonical interactions among contemporaneous variables. This allows consistent inference on the influence of past variables even if the...

We analyze multivariate binary time series using a mixed parameterization in terms of the conditional expectations given the past and the pairwise canonical interactions among contemporaneous variables. This allows consistent inference on the influence of past variables even if the...

An essential problem in nonparametric smoothing of noisy data is a proper choice of the bandwidth or window width, which depends on a smoothing parameter <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$k$$</EquationSource> </InlineEquation>. One way to choose <InlineEquation ID="IEq2"> <EquationSource Format="TEX">$$k$$</EquationSource> </InlineEquation> based on the data is leave-one-out-cross-validation. The selection of the cross-validation criterion is...</equationsource></inlineequation></equationsource></inlineequation>

We analyze multivariate binary time series using a mixed parameterization in terms of the conditional expectations given the past and the pairwise canonical interactions among contemporaneous variables. This allows consistent inference on the influence of past variables even if the...

Prediction of demand for professional sports is increasingly drawing the attention of economists. We apply linear mixed models for modeling attendance figures at Spanish professional football. We investigate economic variables, such as the price of the tickets or the size of the market, and...