It is common to test the null hypothesis that two samples were drawn from identical distributions; and the Smirnov (sometimes called Kolmogorov-Smirnov) test is conventionally applied. We present simulation results to compare the performance of this test with three recently introduced alternatives. We consider both continuous and discrete data. We show that the alternative methods preserve type I error at the nominal level as well as the Smirnov test but offer superior power. We argue for the routine replacement of the Smirnov test with the modified Baumgartner test according to Murakami (2006), or with the test proposed by Zhang (2006).</p
Goodness-of-fit statistics measure the compatibility of random samples against some theoretical or r...
This paper provides extensive simulated power studies for three majorgoodness-of-fit test statistics...
<p>* = p < 0.05</p><p>** = p < 0.01</p><p>*** = p < 0.001.</p><p><b><i>D</i></b> values for pairwise...
It is common to test the null hypothesis that two samples were drawn from identical distributions; a...
The delta-corrected Kolmogorov-Smirnov test has been shown to be uniformly more powerful than the cl...
The classical goodness-of-fit problem, in the case of a null continuous and completely specified dis...
Goodness-of-fit statistics measure the compatibility of random samples against some theoretical prob...
Thesis (M.A.)--Boston UniversityPLEASE NOTE: Boston University Libraries did not receive an Authoriz...
Goodness-of-fit statistics measure the compatibility of random samples against some theoretical prob...
. This paper presents two Bayesian alternatives to the chi-squared test for determining whether a pa...
Goodness-of-fit statistics measure the compatibility of random samples against some theoretical pro...
A modified version of the Kolmogorov-Smirnov (KS) test is presented as a tool to assess whether a sp...
For the two-sample problem with location and/or scale alternatives, as well as different shapes, sev...
Current methods to compare measurement series are based on the comparison of multiple measurement po...
The Kolmogorov-Smirnov (K–S) one-sided and two-sided tests of goodness of fit based on the test stat...
Goodness-of-fit statistics measure the compatibility of random samples against some theoretical or r...
This paper provides extensive simulated power studies for three majorgoodness-of-fit test statistics...
<p>* = p < 0.05</p><p>** = p < 0.01</p><p>*** = p < 0.001.</p><p><b><i>D</i></b> values for pairwise...
It is common to test the null hypothesis that two samples were drawn from identical distributions; a...
The delta-corrected Kolmogorov-Smirnov test has been shown to be uniformly more powerful than the cl...
The classical goodness-of-fit problem, in the case of a null continuous and completely specified dis...
Goodness-of-fit statistics measure the compatibility of random samples against some theoretical prob...
Thesis (M.A.)--Boston UniversityPLEASE NOTE: Boston University Libraries did not receive an Authoriz...
Goodness-of-fit statistics measure the compatibility of random samples against some theoretical prob...
. This paper presents two Bayesian alternatives to the chi-squared test for determining whether a pa...
Goodness-of-fit statistics measure the compatibility of random samples against some theoretical pro...
A modified version of the Kolmogorov-Smirnov (KS) test is presented as a tool to assess whether a sp...
For the two-sample problem with location and/or scale alternatives, as well as different shapes, sev...
Current methods to compare measurement series are based on the comparison of multiple measurement po...
The Kolmogorov-Smirnov (K–S) one-sided and two-sided tests of goodness of fit based on the test stat...
Goodness-of-fit statistics measure the compatibility of random samples against some theoretical or r...
This paper provides extensive simulated power studies for three majorgoodness-of-fit test statistics...
<p>* = p < 0.05</p><p>** = p < 0.01</p><p>*** = p < 0.001.</p><p><b><i>D</i></b> values for pairwise...