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ConfSets.jl is a Julia library for computing confidence intervals using various statistical methods including the Central Limit Theorem (CLT), Hoeffding's Inequality, and Chebyshev's Inequality and confidence sequences. In particular, if you are in a sequential setting, it is advisable to use confidence sequences as over time the confidence intervals will miscover the true mean in multiple instances. On the other hand, the confidence sequences are designed to simultaneously capture the true mean uniformly over time and asymptotically.


You can install ConfSets.jl using the Julia package manager. From the Julia REPL, enter the package manager mode by pressing ], and then run:

add ConfSets


Once installed, you can use the library to compute confidence intervals and confidence sequences using the methods shown below. Notice that if you want to compute sequential confidence sets, you can set the sequential parameter to true, otherwise set it to false.

using ConfSets

data = [10.2, 12.3, 9.8, 11.5, 10.9]
alpha = 0.05

# Compute confidence interval using CLT
clt_interval = confint(data, alpha, "clt", sequential=true)

# Compute confidence interval using Hoeffding's Inequality
# The argument'rang'is the range of the data (e.g. if the distribution is in the range 9-13 --> set rang=4)
hoeffding_interval = confint(data, alpha, "hoeffding", rang=4, sequential=false)

# Compute confidence interval using Chebyshev's Inequality
chebyshev_interval = confint(data, alpha, "chebyshev", sequential=true)

# Compute Asymptotic Confidence Sequence
asymptotic_sequence = confseq(data, alpha, "asymptotic", sequential=true)


Contributions are welcome! If you encounter any issues, have suggestions for improvements, or would like to add new features, feel free to open an issue or submit a pull request on GitHub.


The code is available as open source under the terms of the MIT License.