Initial Guess of Univariate Mixture Components

Heuristic method to guess number of components and their parameters (mean, standard deviation and weight) from observation data.

mx_guess_components(x, bw = 1, minpeak = 0, mincut = 0.9, ...)

Arguments

x

vector of (non-binned) observation data
bw

bandwidth of kernel density, cf. density
minpeak

minimum value of the total maximum which is regarded as peak
mincut

minimum relative height of a pit compared to the lower of the two neighbouring maxima at which these maxima are regarded as separate peaks (default value is derived from golden section)
...

further arguments passed to density

Value

data frame with mean (mean), standard deviation sd and mixing proportions L

Details

The function guesses approximate start values of parameters that then need subsequent identification, e.g. with a maximum likelihood or EM (expectation maximization) method.

See also

peakwindow

Examples


set.seed(123)
x <- c(rnorm(20, 5, 1), rnorm(30, 10, 1), rnorm(50, 20, 2))
hist(x, breaks=20)


mx_guess_components(x)

#>        mean       sd         L
#> 1  5.021476 1.258172 0.1934724
#> 2  9.939100 1.333979 0.3068663
#> 3 20.297907 2.051515 0.4996613