Question 1

How to calculate binomial probability with Probably in Swift?

Accepted Answer

Import the Probably library and use the Binomial distribution structure by initializing it with parameters like trials and success probability. Call methods such as probability mass function for specific calculations, but note that detailed examples are lacking in the README, so refer to the source code for implementation.

Question 2

Does Probably support cumulative distribution functions?

Accepted Answer

Yes, Probably includes cumulative distribution functions for its supported distributions like Gaussian and Poisson, as mentioned in the README for computing probability and cumulative distributions. This allows for common statistical calculations directly in Swift.

Question 3

Probably Swift vs StatsKit for statistical analysis?

Accepted Answer

Probably focuses on probability distributions with a clean interface, while StatsKit offers broader statistical functions including tests and regression. Choose Probably for lightweight distribution calculations in Swift, but opt for StatsKit if you need comprehensive statistical analysis tools. Both integrate with Swift Package Manager.

Question 4

Can I use Probably for machine learning in Swift?

Accepted Answer

Probably is not ideal for machine learning as it only provides basic probability distributions without advanced models like neural networks or optimization algorithms. For ML in Swift, consider libraries like TensorFlow Swift or more specialized frameworks that build on statistical foundations.

Question 5

Is Probably suitable for iOS app development?

Accepted Answer

Yes, Probably is suitable for iOS app development as it's a pure Swift library that integrates via Swift Package Manager, enabling probabilistic calculations in apps. However, its limited scope means you might need additional libraries for full data analysis or visualization features.

Question 6

How to handle continuous distributions with Probably?

Accepted Answer

Use the Continuous distribution structure in Probably to model continuous probability distributions by specifying parameters. It supports functions like probability density, but due to sparse documentation, you may need to examine the source code for specific usage patterns and implementation details.

Probably

What is Probably?

Overview

Use Cases

Best For

Related Projects

Found a gem we're missing?

Not Ideal For

Pros & Cons

Pros

Cons

Frequently Asked Questions