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| OptSig-package | Optimal Level of Significance for Regression and Other Statistical Tests |
| data1 | Data for the U.S. production function estimation |
| Opt.Sig | Optimal Significance Level for an F-test |
| Opt.sig.2p.test | Optimal significance level calculation for the test for two proportions (same sample sizes) |
| Opt.sig.2p2n.test | Optimal significance level calculation for the test for two proportions (different sample sizes) |
| Opt.sig.anova.test | Optimal significance level calculation for balanced one-way analysis of variance tests |
| Opt.Sig.Chisq | Optimal Significance Level for a Chi-square test |
| Opt.sig.chisq.test | Optimal significance level calculation for chi-squared tests |
| Opt.sig.norm.test | Optimal significance level calculation for the mean of a normal distribution (known variance) |
| Opt.sig.p.test | Optimal significance level calculation for proportion tests (one sample) |
| Opt.sig.r.test | Optimal significance level calculation for correlation test |
| Opt.sig.t.test | Optimal significance level calculation for t-tests of means (one sample, two samples and paired samples) |
| Opt.sig.t2n.test | Optimal significance level calculation for two samples (different sizes) t-tests of means |
| Opt.SigBoot | Optimal Significance Level for the F-test using the bootstrap |
| Opt.SigBootWeight | Weighted Optimal Significance Level for the F-test based on the bootstrap |
| Opt.SigWeight | Weighted Optimal Significance Level for the F-test based on the assumption of normality in the error term |
| OptSig | Optimal Level of Significance for Regression and Other Statistical Tests |
| Power.Chisq | Function to calculate the power of a Chi-square test |
| Power.F | Function to calculate the power of an F-test |
| R.OLS | Restricted OLS estimation and F-test |