Non-central Chi Square Distribution
The non-central chi square (χ2) distribution, also known as the generalized chi square distribution, is a generalization of the chi square distribution. It is used in the power analysis of statistical tests, including likelihood ratio tests.
Definition
The non-central chi square distribution with
where
The parameters must satisfy
Applications
Statistical power analysis uses it for chi-square and F-tests.
Signal processing employs it in radar detection theory.
Quality control uses it in process monitoring.
Properties
Property | Value |
---|---|
Mean | |
Variance | |
Skewness | |
Excess Kurtosis | |
Mode |
Notable properties include:
The characteristic function is
.The distribution is always right-skewed.
The moment generating function is
.
Relationships to Other Distributions
When
, it reduces to the central chi-square distribution.It is the distribution of the sum of squares of independent normal variables with non-zero means.
For large
, it approaches a normal distribution.
The NonCentralChiSquareDistribution class
The non-central chi square distribution is implemented by the NonCentralChiSquareDistribution class. It has one constructor which takes the degrees of freedom and the non-centrality parameter as arguments. The following constructs a non-central chi square distribution with 10 degrees of freedom and non-centrality parameter 15:
var ncChiSquare = new NonCentralChiSquareDistribution(10, 15);
The NonCentralChiSquareDistribution class has two specific properties. DegreesOfFreedom returns the degrees of freedom of the distribution. NonCentralityParameter returns the non-centrality parameter.
References
Johnson, N. L., Kotz, S., & Balakrishnan, N. (1995). Continuous Univariate Distributions, Volume 1 (2nd ed.). Wiley.
Mood, A. M., Graybill, F. A., & Boes, D. C. (1974). Introduction to the Theory of Statistics (3rd ed.). McGraw-Hill.