EnvironmentalStats for S-PLUS

Feature List

Because EnvironmentalStats for S-PLUS is an S-PLUS module, you automatically have access to all the features and functions of S-PLUS, including powerful graphics, standard hypothesis tests, and the flexibility of a programming language. In addition, specific features of EnvironmentalStats for S-PLUS include the following:

Pull-Down Menu

Additional Probability Distributions

Chi (square root of a chi-square)
Empirical
Extreme Value
Generalized Extreme Value
3-Parameter Lognormal
Mixture of Two Lognormals
Truncated Lognormal
Mixture of Two Normals
Truncated Normal
Pareto
Non-central Student's t
Triangular
Zero-Modified Lognormal (Also Called the Delta Distribution; Lognormal with positive mass at 0)
Zero-Modified Normal (Normal with positive mass at 0)

Probability Density and Cumulative Distribution Plots

See how the pdf and cdf change with distribution parameters
Add theoretical pdf to histogram
Add theoretical cdf to empirical cdf plot

Q-Q Plots for All Probability Distributions

Standard Q-Q Plots
Tukey Mean-Difference Plots
Q-Q Plot Gestalt Function to Produce Numerous "Typical" Q-Q Plots

Estimation of Distribution Parameters and Quantiles

Maximum Likelihood
Minimum Variance Unbiased
Method of Moments
Method of L-Moments

Confidence Intervals for Distribution Parameters and Quantiles

Additional Goodness-of-Fit Tests

Probability Plot Correlation Coefficient
Shapiro-Francia
Shapiro-Wilk
Results Can Be Plotted. Optional Plots Include:

Histogram with Overlaid Fitted Distribution
Q-Q Plot
CDF Plots of Observed and Fitted Distribution
Test Results

Prediction and Tolerance Intervals

Methods for Type I Singly and Multiply Censored Data

Empirical Cumulative Distribution Plots
Quantile-Quantile (Probability) Plots
Goodness-of-Fit Tests
Estimation, Hypothesis Testing, and Confidence Intervals

Special Hypothesis Tests

Seasonal Kendall Test for Trend
Quantile Test (Detects Shifts in Tail of Distribution)

Sample Size and Power Calculations and Plots

Tools for Probabilistic Risk Assessment

Simple Random Sampling and Latin Hypercube Sampling
Generate Random Numbers from a Multivariate Normal Distribution
Generate a Multivariate Matrix from One or More Specified Distributions with a Specified Rank Correlation
Create an Output Distribution of Exposure or Risk

Built-In Data Sets

Data Sets Appearing in Selected EPA Guidance Documents
Selected Data Sets from the Environmental Statistics Literature

Extensive Hypertext Help System

Functions Like an Electronic Text Book
Cross-Referenced Help Files that Clearly Explain Each Procedure and Provide Specific, Detailed Examples
Detailed Abstracts of Selected Literature in Environmental Statistics
A Fully Cross-Referenced, Hypertext Glossary of Statistical and Environmental Terms