For simulation setting (3), 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 (4), 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
Scenario descriptions and parameter combinations are adapted directly from Ioannidis [1]. The remain...
The output from simulation factorial experiments can be complex and may not be amenable to standard ...
<p>The figure plots the mean (A) genotype error and (B) clone frequency error as a function of the...
For simulation setting (1), shown are the RSSEs of the estimated joint probabilities to the true val...
<p>The first to third columns denote the effect sizes of SNP1, SNP2 and interaction in pure samples ...
<p>The upper and lower figures show the results when the number of samples is equal to 1,000 and 3,0...
A: Illustration of the L1 (blue) and (red) distances between two distributions. The green dotted li...
<p>The upper figures show the results when the number of samples is equal to 1000 and the lower figu...
(A) Designed data distributions of the three-dimensional data of 20 x 20 x 20 categories from two-le...
Simulation techniques must be able to generate the types of distributions most commonly encountered ...
Simulation techniques must be able to generate the types of distributions most commonly encountered ...
(A) Designed data distribution of the three-dimensional data of 20 x 20 x 20 categories from normal ...
A: Encoding models used in simulation 1. B: Steps taken in each repetition of simulation 1. See main...
<p>Top to bottom: Prevalence of MDE, Prevalence of GAD, Odds ratio, Cronbach' alpha. Densities of ne...
<p>The results shown here were obtained using the projection method described in the text. A: Averag...
Scenario descriptions and parameter combinations are adapted directly from Ioannidis [1]. The remain...
The output from simulation factorial experiments can be complex and may not be amenable to standard ...
<p>The figure plots the mean (A) genotype error and (B) clone frequency error as a function of the...
For simulation setting (1), shown are the RSSEs of the estimated joint probabilities to the true val...
<p>The first to third columns denote the effect sizes of SNP1, SNP2 and interaction in pure samples ...
<p>The upper and lower figures show the results when the number of samples is equal to 1,000 and 3,0...
A: Illustration of the L1 (blue) and (red) distances between two distributions. The green dotted li...
<p>The upper figures show the results when the number of samples is equal to 1000 and the lower figu...
(A) Designed data distributions of the three-dimensional data of 20 x 20 x 20 categories from two-le...
Simulation techniques must be able to generate the types of distributions most commonly encountered ...
Simulation techniques must be able to generate the types of distributions most commonly encountered ...
(A) Designed data distribution of the three-dimensional data of 20 x 20 x 20 categories from normal ...
A: Encoding models used in simulation 1. B: Steps taken in each repetition of simulation 1. See main...
<p>Top to bottom: Prevalence of MDE, Prevalence of GAD, Odds ratio, Cronbach' alpha. Densities of ne...
<p>The results shown here were obtained using the projection method described in the text. A: Averag...
Scenario descriptions and parameter combinations are adapted directly from Ioannidis [1]. The remain...
The output from simulation factorial experiments can be complex and may not be amenable to standard ...
<p>The figure plots the mean (A) genotype error and (B) clone frequency error as a function of the...