Nonparametric Estimation
Nonparametric estimation is a statistical method that does not assume a specific form for the underlying distribution of the data. Instead of fitting data to a predetermined model, it allows for more flexibility by using the data itself to estimate the distribution. This approach is particularly useful when the true distribution is unknown or when the sample size is small.
Common techniques in nonparametric estimation include kernel density estimation and histograms. These methods can provide insights into the shape and characteristics of the data without relying on strict assumptions, making them valuable tools in exploratory data analysis and various fields such as economics and biology.