Assigning numerical values to categorical (factor) variables is called contrast coding. This need arises when we want to estimate the difference in the dependent variable among different conditions of an independent variable. In other words, we use contrast coding to instruct the Bayesian model to compare the conditional means between different conditions or bundles ofContinue reading “Contrast coding”
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Beta-Binomial distribution
Beta-binomial distribution is a discrete probability distribution. It is basically a Binomial distribution when probability of success at each of the “future” n Bernoulli trials is not fixed but drawn from a Beta distribution. Beta-binomial distribution is used to capture overdispersion in Binomial type distributed data. There are 3 parameters in Beta-binomial: n, the futureContinue reading “Beta-Binomial distribution”
Log-normal distribution
The log-normal distribution is a continuous probability distribution of a positive real random variable, whose logarithm is normally distributed. It is often used to model right-skewed (long right tail), none-negative data. A Log-normal distribution is defined by the locationand scalethat coincide with the mean and standard deviation of the log-transformed normal distribution. As they areContinue reading “Log-normal distribution”
Bivariate and Multivariate distributions
Univariate distributions display probability distribution for one variable, such as the number of desirable events in Binomial distribution, the variable having mean and standard deviation in Normal distribution, and the probability for each Bernoulli event in a Beta distribution. A bivariate or multivariate distribution defines probability for two or more dimensions. Assuming a PMF isContinue reading “Bivariate and Multivariate distributions”
Guest on the snow mountain 