Let T be the Student one- or two-sample t-, F-, or Welch statistic. Now release the underlying assumptions of normality, independence and identical distribution and consider a more general case where one only assumes that the vector of data has a continuous joint density. We determine asymptotic expressions for P(T > u) as u -> infinity for this case. The approximations are particularly accurate for small sample sizes and may be used, for example, in the analysis of High-Throughput Screening experiments, where the number of replicates can be as low as two to five and often extreme significance levels are used. We give numerous examples and complement our results by an investigation of the convergence speed - both theoretically, by deriving ...
Typescript (photocopy).A set of multivariate observations is said to satisfy a linear functional rel...
An asymptotic expansion of the Student t distribution is derived by expanding the standardized Stude...
An asymptotic expansion of the Student t distribution is derived by expanding the standardized Stude...
Let T be the Student one- or two-sample t-, F-, or Welch statistic. Now release the underlying assum...
Let T be the Student one- or two-sample t-, F-, or Welch statistic. Now release the underlying assum...
Let X1,..., Xn be i.i.d. random observations, taking their values in a measurable space. Consider a ...
AbstractWe derive asymptotic expansions for the distributions of the normal theory maximum likelihoo...
In this paper, we develop a local limit theorem for the Student distribution. We use it to improve t...
In the analysis of microarray data, and in some other contemporary statistical problems, it is not u...
In the analysis of microarray data, and in some other contemporary statistical problems, it is not u...
The T-test is probably the most popular statistical test; it is routinely recommended by the textboo...
This paper derives an explicit approximation for the tail probability of a sum of sample v...
The sampling distribution of several commonly occurring statistics are known to be closer to the cor...
In the paper, we discuss the transformation of the asymptotic expansion for the distribution of a st...
In the paper, we discuss the transformation of the asymptotic expansion for the distribution of a st...
Typescript (photocopy).A set of multivariate observations is said to satisfy a linear functional rel...
An asymptotic expansion of the Student t distribution is derived by expanding the standardized Stude...
An asymptotic expansion of the Student t distribution is derived by expanding the standardized Stude...
Let T be the Student one- or two-sample t-, F-, or Welch statistic. Now release the underlying assum...
Let T be the Student one- or two-sample t-, F-, or Welch statistic. Now release the underlying assum...
Let X1,..., Xn be i.i.d. random observations, taking their values in a measurable space. Consider a ...
AbstractWe derive asymptotic expansions for the distributions of the normal theory maximum likelihoo...
In this paper, we develop a local limit theorem for the Student distribution. We use it to improve t...
In the analysis of microarray data, and in some other contemporary statistical problems, it is not u...
In the analysis of microarray data, and in some other contemporary statistical problems, it is not u...
The T-test is probably the most popular statistical test; it is routinely recommended by the textboo...
This paper derives an explicit approximation for the tail probability of a sum of sample v...
The sampling distribution of several commonly occurring statistics are known to be closer to the cor...
In the paper, we discuss the transformation of the asymptotic expansion for the distribution of a st...
In the paper, we discuss the transformation of the asymptotic expansion for the distribution of a st...
Typescript (photocopy).A set of multivariate observations is said to satisfy a linear functional rel...
An asymptotic expansion of the Student t distribution is derived by expanding the standardized Stude...
An asymptotic expansion of the Student t distribution is derived by expanding the standardized Stude...