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Professor K. Krishnamoorthy
[Dept of Mathematics, UL Lafayette, Lafayette, Louisiana, USA]
 

StatCalc 2.0

Updated on 12/03/06

StatCalc 3.0 (01/24/2014)

Description: StatCalc is a PC calculator that computes table values of many commonly used statistical distributions. It also computes moments, and many other statistics; see the table of content. Download and click on setup.exe. StatCalc also comes with help files.

 

Table of Content

Operating Systems: Windows 7, XP, 2000; Windows 8 (some components may not work). Disk space : 10 MB

 

Fortran Programs... Comments to krishna@louisiana.edu

1. Noncentral t

Fortran program to evaluate the cdf of the noncentral t [Benton, D. and Krishnamoorthy, K. (2003). Computing discrete mixtures of continuous distributions: noncentral chisquare, noncentral t and the distribution of the square of the sample multiple correlation coefficient. Computational Statistics and Data Analysis, 43, 249-267]

2. Noncentral chi-square

Fortran program to evaluate the cdf of the noncentral chi-square [ Benton, D. and Krishnamoorthy, K. (2003)]

3. Two Proportions

Fortran program: computes the p-value for testing the difference between proportions from two finite populations. [Krishnamoorthy, K. and Thomson, J. (2002). Hypothesis testing about proportions in two finite populations. The American Statistician, 56, (2002), 215-222.]

4. Power : Two Proportions

Fortran program: computes the power of the test (3) for the difference between proportions from two finite populations. [Krishnamoorthy, K. and Thomson, J. (2002)]

5. Two Poisson Means

Fortran program: computes the p-value for testing the difference between two Poisson means. [Source: Krishnamoorthy, K and Thomson, J. (2004) A more powerful test for comparing two Poisson means. Journal of Statistical Planning and Inference, 119, 249-267]

6. Power: Two Poisson Means

Fortran program: computes the power of the unconditional test for the difference between two Poisson means. [Krishnamoorthy, K and Thomson, J. (2004) A more powerful test for comparing two Poisson means. Journal of Statistical Planning and Inference, 119, 249-267]

7. Lognormal mean

SAS code

Fortran program: computes confidence limits for the mean of a lognormal distribution. [Krishnamoorthy, K. and Mathew, T. (2003) Inferences on the means of lognormal distributions using generalized p-values and generalized confidence intervals. Journal of Statistical Planning and Inference, (2003), 115, 103 – 121] Help7.pdf

8. Power: Lognormal mean

SAS code

Computes the power of the test in (7). For a given mean and standard deviation of the logged data, and the sample size, this program computes the power of the test in (7). Help8.pdf

9. Lognormal: Two-sample

SAS code

Computes the p-value for testing the difference between two lognormal means. Also, computes the confidence interval for the difference between the means. Help9.pdf

10. Lognormal: Power for Two-sample Test

SAS code

Computes the power of the test (9) for testing the difference between two lognormal means. Help10.pdf

11. One-sided limits for exceedance probabilities

SAS code

Computes the one-sided limits for the exceedance probabilities assuming random effects model. See

Krishnamoorthy, K. Mathew, T.  and Ramachandran, G. (2007). Upper limits for the exceedance probabilities in one-way random effects model.  Annals of Occupational Hygiene, 51, 397-406.

12. R program                      EXPOSURE_MDLS.r; help file

Krishnamoorthy, K. and Zhao Zu (2011). Confidence Limits for Lognormal Percentiles and for Lognormal Mean based on Samples with Multiple Detection Limits. Annals of Occupational Hygiene, 55,  495-509. 

Krishnamoorthy, K., Mathew, T. and Zhao Xu (2012).  Tests for an Upper Percentile of a Lognormal Distribution Based on Samples with Multiple Detection Limits and Sample Size Calculation. Submitted.

13. GammaInfer.r

This R program computes confidence intervals for gamma parameters and mean, CIs for the difference between two means, difference between two shape parameters. Also, calculates the p-values for testing the mean and parameters, comparing two means, two scale parameters and for comparing two shape parameters.

 

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