For simulation setting (1), shown are the RSSEs of the estimated joint probabilities to the true values (A) as a function of sample sizes with a fixed number of categories, and (B) as a function of various numbers of categories with a fixed sample size. For simulation setting (2), shown are the estimation RSSEs (C) as a function of sample sizes and (D) as a function of numbers of categorical values. The RSSEs of the proposed method are shown in solid lines, and those of conventional combination-wise estimation are shown in dashed lines. The average RSSEs from 100 repeated simulations are shown with dots and the standard deviation is shown with error bars.</p
The data is a simulation of confidence limits, coverage probabilities, average difference from actua...
Input data modeling is a critical component of a successful simulation application. A perspective of...
<p>This shows the performance of the three different methods (MELD, t+TFCER, and t-test) using three...
For simulation setting (3), shown are the RSSEs of the estimated joint probabilities to the true val...
(A) Designed data distributions of the three-dimensional data of 20 x 20 x 20 categories from two-le...
A: Illustration of the L1 (blue) and (red) distances between two distributions. The green dotted li...
A: Encoding models used in simulation 1. B: Steps taken in each repetition of simulation 1. See main...
<p>(A) MI estimation using the binning method with QE correction, as a function of the number of bin...
An important, but often neglected, part of any sound simulation study is that of modeling each sourc...
<p>Saturation marginal probability distributions from simulations of systems of territorial central ...
<p>This shows the performance of the three different methods (MELD, t+TFCER, and t-test) using three...
This paper considers simulation estimation of sample selection models. Simulation estimation techniq...
<p>Dispersions with gene-wise log geometric mean counts below the median (log mean from 2.17 to 1.63...
<p>The same set of initial conditions as for the <a href="http://www.plosone.org/article/info:doi/10...
The statistics profession has been remiss in exploiting the numerous advances in simulation methodol...
The data is a simulation of confidence limits, coverage probabilities, average difference from actua...
Input data modeling is a critical component of a successful simulation application. A perspective of...
<p>This shows the performance of the three different methods (MELD, t+TFCER, and t-test) using three...
For simulation setting (3), shown are the RSSEs of the estimated joint probabilities to the true val...
(A) Designed data distributions of the three-dimensional data of 20 x 20 x 20 categories from two-le...
A: Illustration of the L1 (blue) and (red) distances between two distributions. The green dotted li...
A: Encoding models used in simulation 1. B: Steps taken in each repetition of simulation 1. See main...
<p>(A) MI estimation using the binning method with QE correction, as a function of the number of bin...
An important, but often neglected, part of any sound simulation study is that of modeling each sourc...
<p>Saturation marginal probability distributions from simulations of systems of territorial central ...
<p>This shows the performance of the three different methods (MELD, t+TFCER, and t-test) using three...
This paper considers simulation estimation of sample selection models. Simulation estimation techniq...
<p>Dispersions with gene-wise log geometric mean counts below the median (log mean from 2.17 to 1.63...
<p>The same set of initial conditions as for the <a href="http://www.plosone.org/article/info:doi/10...
The statistics profession has been remiss in exploiting the numerous advances in simulation methodol...
The data is a simulation of confidence limits, coverage probabilities, average difference from actua...
Input data modeling is a critical component of a successful simulation application. A perspective of...
<p>This shows the performance of the three different methods (MELD, t+TFCER, and t-test) using three...