Sentence examples for random indicators from inspiring English sources

For instance, an explicit expression for the orthogonal polynomials associated to general sums of independent random indicators seems to be unknown.

Upper bounds for the Kolmogorov distance in Poisson approximation for sums of independent random indicators have been obtained by many authors using different techniques.

This transformation can be done by filtering the randomness produced by the disturbance by means of a statistic applied to the random indicator i.

Factor variances were free to vary, while one random indicator regression weight was constrained to 1.0 per latent construct.

These models simultaneously include fixed indicators that enable ORs to be calculated, as in the standard models, and a random indicator, inter-GP variance, which allows us to calculate variations in the agreement rates between GPs [ 19].

We generated a random (yes/no) indicator of illness, I ij, based on the number of pathogens and the probability of illness given P ij.

For nearly 60 years now, Ernie - the UK's official electronic random-number-indicator - has been whirring away picking the month's prize-winning Premium Bonds.

Random effects included indicators for twin pairs, for P-versus-U comparisons, and for the strata defined by the matching variables for the P-versus-C and U-versus-C comparisons.

The indicator values were broadly consistent over three years; the lack of random variation indicates some consistency in coding.

This problem corresponds to a simple 2-way contingency table with two indicator random variables X and Y. Variable X indicates genes ranked among the top- L1 in the list of the first TF and variable Y indicates genes ranked among the top- L2 in the target gene list of the second TF.

Hypothesis tests and confidence intervals for population variances, chi-squared goodness-of-fit tests, hypothesis tests for independence, simple linear regression model, testing regression parameters, prediction, multiple regression, omitted variable bias, multicollinearity, F-tests, regression with indicator random variables, simultaneous equation models and instrumental variables.