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In general under complete randomization, if the number of units interfering with a unit is of the same order as the sample size, our view of the unit’s potential outcomes will
The zero-centered heavy-tailed prior distribution on w induces sparsity in the parameters vector, while the adaptive mixture model applied on the weight centers m forces a
In the ordinal regression model, we trained with soft thresholds since we needed the model to be differentiable end to end. In the post-hoc model, we searched threshold space in
The second estimator relaxes the Gaussian assumption and allows both the running variable and measurement error to follow arbitrary distributions characterized by finite numbers
In doing so, we introduce the basic meaning and relevance of the judgment to regard a sequence of quantities exchangeably, and we show how the fundamental theorem of probability can
Unlike its predecessors the main attraction of the LL distribution is that it has nice compact forms for the probability density function (pdf), cdf and
For community detection, the focus is on the special case where all π i are degenerate; the goal is clustering, so Hamming distance is the natural choice of loss function, and the
The better performance of moncord over space, concord and glasso is largely due to the fact that mconcord is designed for multivariate network, and treating the precision matrix
