NAG FL Interface
G07 (Univar)
Univariate Estimation

G07 (Univar) Chapter Introduction – A description of the Chapter and an overview of the algorithms available.

Routine
Mark of
Introduction

Purpose
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15 nagf_univar_ci_binomial
Computes confidence interval for the parameter of a binomial distribution
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15 nagf_univar_ci_poisson
Computes confidence interval for the parameter of a Poisson distribution
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15 nagf_univar_estim_normal
Computes maximum likelihood estimates for parameters of the Normal distribution from grouped and/or censored data
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15 nagf_univar_estim_weibull
Computes maximum likelihood estimates for parameters of the Weibull distribution
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23 nagf_univar_estim_genpareto
Estimates parameter values of the generalized Pareto distribution
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15 nagf_univar_ttest_2normal
Computes t-test statistic for a difference in means between two Normal populations, confidence interval
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13 nagf_univar_robust_1var_median
Robust estimation, median, median absolute deviation, robust standard deviation
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13 nagf_univar_robust_1var_mestim
Robust estimation, M-estimates for location and scale parameters, standard weight functions
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13 nagf_univar_robust_1var_mestim_wgt
Robust estimation, M-estimates for location and scale parameters, user-defined weight functions
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14 nagf_univar_robust_1var_trimmed
Computes a trimmed and winsorized mean of a single sample with estimates of their variance
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16 nagf_univar_robust_1var_ci
Robust confidence intervals, one-sample
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16 nagf_univar_robust_2var_ci
Robust confidence intervals, two-sample
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23 nagf_univar_outlier_peirce_1var
Outlier detection using method of Peirce, raw data or single variance supplied
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23 nagf_univar_outlier_peirce_2var
Outlier detection using method of Peirce, two variances supplied