mixnorm function

Parameter Estimation for Uni- or Multivariate Normal Mixture Models

`mixnorm' is used to estimate parameters of a normal mixture model with equal variance. The function supports both one-dimensional and multi-dimensional data.

mixnorm(x, C = 2, sigma.known = NULL, ini = NULL, tol = 1e-05)

Arguments

• x: an n by p matrix of observations where n is the number of observations and s is the dimension of data.
• C: number of mixture components. Default is 2.
• sigma.known: a vector or matrix of component standard deviations. Default is NULL, which means the standard deviations are unknown.
• ini: initial values for the parameters. Default is NULL, which randomly sets the initial values using the given observations. If specified, it can be a list with the form of list(mu, pi, sigma), where mu is a vector of C component means, pi is a vector of C mixing proportions, and sigma is a vector of C component standard deviations (this element is only needed when sigma.known is not given).
• tol: stopping criteria for the algorithm. Default is 1e-05.

Returns

A list containing the following elements: - mu: estimated component means.

• sigma: estimated component standard deviations. Only returned when sigma.known is not specified.

• pi: estimated mixing proportions.

• p: matrix containing estimated classification probabilities where the (i, j)th element is the probability of the jth observation belonging to the ith component.

• lik: final likelihood.

Examples

# See examples for the `complh' function.

See Also

complh, distlat