6.33 G07 Univariate Estimation

g07 - Univariate Estimation

g07 Chapter Introduction

Routine Name Mark of Introduction Purpose
g07aac 7 nag_binomial_ci
Computes confidence interval for the parameter of a binomial distribution
g07abc 7 nag_poisson_ci
Computes confidence interval for the parameter of a Poisson distribution
g07bbc 7 nag_censored_normal
Computes maximum likelihood estimates for parameters of the Normal distribution from grouped and/or censored data
g07bec 7 nag_estim_weibull
Computes maximum likelihood estimates for parameters of the Weibull distribution
g07bfc 9 nag_estim_gen_pareto
Estimates parameter values of the generalized Pareto distribution
g07cac 4 nag_2_sample_t_test
Computes t-test statistic for a difference in means between two Normal populations, confidence interval
g07dac 3 nag_median_1var
Robust estimation, median, median absolute deviation, robust standard deviation
g07dbc 4 nag_robust_m_estim_1var
Robust estimation, M-estimates for location and scale parameters, standard weight functions
g07dcc 7 nag_robust_m_estim_1var_usr
Robust estimation, M-estimates for location and scale parameters, user-defined weight functions
g07ddc 4 nag_robust_trimmed_1var
Trimmed and winsorized mean of a sample with estimates of the variances of the two means
g07eac 7 nag_rank_ci_1var
Robust confidence intervals, one-sample
g07ebc 7 nag_rank_ci_2var
Robust confidence intervals, two-sample
g07gac 23 nag_outlier_peirce
Outlier detection using method of Peirce, raw data or single variance supplied
g07gbc 23 nag_outlier_peirce_two_var
ROutlier detection using method of Peirce, two variances supplied