variate

The same process is carried out with the y variate.

It is also natural to use a control variate.

Third, the predictors are added together; the sum is called the variate.

Their colors are a variate of blue and white.

The dimension measured is called the variate and may be any physical quantity.

The behavior of a when the variates have other distributions is currently unknown.

This property can be used for generating antithetic variates, among other things.

Let Z be a normally distributed variate with a mean 0 and variance of 1.

Let U be a random variate from the standard uniform distribution.

This variate is used as the predictor of the outcome, also expressed in z scores.

The mode of a variate X distributed as is .

Assume also that the likelihood of a variate being chosen is proportional to its value.

The first sample is chosen with probability proportional to the size of the x variate.

The variates do not have to be identically or symmetrically distributed.

Let X be a t distributed random variate with k degrees of freedom.

The value of this variation is that the variate is already in z score form.

If the variates have a normal or a uniform distribution the distribution of a is the same.

If library routines are available to generate the requisite gamma variate directly, they may be used instead.

Specialized techniques such as "control variates" and "importance sampling" have been developed to speed simulation.

The terminology here is the same as that for random variable and random variate.

It may be worth noting that the mean and the mode coincide if the variates are normally distributed.

The use of the antithetic variates method to estimate the result shows an important variance reduction.

The relationship of this variate to the outcome is assessed with the Pearson R correlation.

The ziggurat algorithm is a fast method for generating exponential variates.

For the generation of non-uniform random variates, see pseudo-random number sampling.