This paper presents practical methods for the sequential generation or simulation of a Gaussian two-dimensional random field. The specific realizations typically correspond to geospatial errors or perturbations over a horizontal plane or grid. The errors are either scalar, such as vertical errors, or multivariate, such as x, y, and z errors. These realizations enable simulation-based performanc...

Data were weights of F1 calves and weaning weights of top-cross progeny from sires and maternal grandsires of 13 breeds. Three analyses were performed on each trait to obtain estimates and standard errors of breed effects needed to calculate across-breed EPD and accuracies. Model (R) for records of F1 progeny contained fixed effects for birth year and date of birth, sex, age and breed of dam, a...

Non-uniform random variate generators are of fundamental importance in Monte-Carlo methods and stochastic simulation. They are based on the assumption that a source of uniformly distributed random numbers is available that produces real and truely random numbers. In practice, however, we have to use pseudo-random numbers which are generated by means of floating point numbers. Thus there are dev...

medication error (me) is the most common preventable cause of adverse drug events which negatively affects patient safety. inadequate, low-quality studies plus wide estimation variations in me from developing countries including iran, decreases the reliability of me evaluations. to clarify sources, underreporting reasons and preventive measures of mes, we reviewed iran current available literat...

We show that linear congruential pseudo-random-number generators can cause systematic errors in Monte Carlo simulations using the Swendsen-Wang algorithm, if the lattice size is a multiple of a very large power of 2 and one random number is used per bond. These systematic errors arise from correlations within a single bond-update half-sweep. The errors can be eliminated (or at least radically r...

This paper is concerned with a semiparametric partially linear regression model with unknown regression coefficients, an unknown nonparametric function for the non-linear component, and unobservable serially correlated random errors. The random errors are modeled by an autoregressive time series. We show that the distributions of the feasible semiparametric generalized least squares estimator o...

Considering the statement that errors can affect the quality of translations, the need to adopt an objective model to analyze these errors has been one of the most debated issues in translation quality assessment. In recent decades, some objective models have emerged with an error analysis nature according to which evaluators can make decisions on the quality of translations. In this study, Met...