CDFs were estimated as Gumbel functions using kernel density estimation35on condition-pooled data. Pairwise comparisons reflecting main and interaction effects of all within- and between-participants factors of the mixed ANOVA design were performed by subtraction of CDFs. Non-parametric statistical evalua...
s correct value from the color value selected on the color wheel on a given trial. The resulting response error distributions were modeled as a mixture of a circular normal distribution and a uniform distribution using maximum likelihood estimation (as described in4). Model fits were separately ...
Explain how to calculate the Maximum Likelihood Estimation of a gamma distribution. Explain how to do the Bernoulli with the binomial distribution. Suppose the distribution of Y conditional on X = x is N(x,x2) and that the marginal distribution of X is uniform (0,1). Find EY, Var(Y) ...
The psychometric quality of the measurement model was assessed using confirmatory factor analysis. For this purpose, a robust maximum likelihood estimator with Satorra-Bentler correction (Satorra & Bentler,1994) and robust standard errors and scaled fit indices were estimated with R lavaan (R Core Tea...
Explain how to calculate the Maximum Likelihood Estimation of a gamma distribution. Suppose that Y has density function f ( y ) = { k y ( 1 ? y ) , 0 ? y ? 1 0 , elsewhere . Find the .95-quantile ? .95 , such that P ( Y ? ? .95 ) = .95 . ...
To understand the relationship between skull evolution and ecological attributes, we reconstructed the evolutionary history of elevation and lifestyle in pikas based on maximum likelihood estimation using the ace function from the ape r package (Paradis & Schliep, 2018). We compared three models of ...
The Baum-Welch algorithm only guarantees reaching a local rather than global maximum of the likelihood. Hence, for each session, after selecting the number of pattern M∗ as above, we ran 20 independent HMM fits on the whole session, with random initial guesses for emission and transition pro...
The logistic regression models were estimated using the Maximum Likelihood Estimation (MLE) method, appropriated for binary dependent variables. OLS regression models Ordinary Least Squares (OLS) regression models were used to estimate wage gaps for the overall sample of academic staff and the subsampl...
The model is then estimated via maximum likelihood techniques using quarterly data from 1960q1 to 1997q2. In this study, we reproduce the central results of Ireland (1999) using the Metropolis–Hastings algorithm. Although we apply Bayesian instead of classical estimation, posterior parameter ...
Ancestral area estimations with a maximum-likelihood Dispersal-Extinction-Cladogenesis (DEC29) model inferred an ancestral range at the root of Nymphalidae covering Southeast Asia, Palearctic and western Nearctic in the Cretaceous (Supplementary Methods 3, Supplementary Figure 3, Supplementary Table 3)....