# confintr The `confintr` package offers classic and/or bootstrap confidence intervals for the following parameters:

• mean,

• quantiles incl. median,

• proportion,

• variance and standard deviation,

• skewness and kurtosis,

• R-squared and the non-centrality parameter of the F distribution,

• Cramér's V and the non-centrality parameter of the chi-squared distribution,

• the odds ratio of a 2x2 table,

• Pearson-, Spearman-, Kendall correlation coefficients,

• mean, quantile and median differences.

Both one- and two-sided intervals are supported.

Different types of bootstrap intervals are possible through argument `boot_type`, see vignette.

## Installation

From CRAN:

``````install.packages("confintr")
``````

``````library(devtools)
install_github("mayer79/confintr")
``````

## Teaser

``````library(confintr)

# Mean
ci_mean(1:100)

# Two-sided 95% t confidence interval for the population mean
#
# Sample estimate: 50.5
# Confidence interval:
#     2.5%    97.5%
# 44.74349 56.25651

# Mean using the Bootstrap
ci_mean(1:100, type = "bootstrap")

#   Two-sided 95% bootstrap confidence interval for the population mean
#   based on 9999 bootstrap replications and the student method
#
# Sample estimate: 50.5
# Confidence interval:
#     2.5%    97.5%
# 44.89255 56.31045

# 95% value at risk
ci_quantile(rexp(1000), q = 0.95)

#   Two-sided 95% binomial confidence interval for the population 95%
#   quantile
#
# Sample estimate: 2.954119
# Confidence interval:
#     2.5%    97.5%
# 2.757986 3.368160

# Mean difference
ci_mean_diff(1:100, 2:101)

#   Two-sided 95% t confidence interval for the population value of mean(x)-mean(y)
#
# Sample estimate: -1
# Confidence interval:
#      2.5%     97.5%
# -9.090881  7.090881

ci_mean_diff(1:100, 2:101, type = "boot", seed = 1)

# Two-sided 95% bootstrap confidence interval for the population value of mean(x)-mean(y)
# based on 9999 bootstrap replications and the student method
#
# Sample estimate: -1
# Confidence interval:
#      2.5%     97.5%
# -9.020367  7.040650

# Further examples (without output)

# Correlation
ci_cor(iris[1:2], method = "spearman", type = "bootstrap")

# Proportions
ci_proportion(10, n = 100, type = "Wilson")
ci_proportion(10, n = 100, type = "Clopper-Pearson")

# R-squared
fit <- lm(Sepal.Length ~ ., data = iris)
ci_rsquared(fit, probs = c(0.05, 1))

# Kurtosis
ci_kurtosis(1:100)

# Mean difference
ci_mean_diff(10:30, 1:15)
ci_mean_diff(10:30, 1:15, type = "bootstrap", R  = 999)

# Median difference
ci_median_diff(10:30, 1:15, R  = 999)
``````

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confintr documentation built on Jan. 29, 2022, 1:08 a.m.