CLUSTER {unknown}R Documentation

CLUSTER Method for Detecting Pulse Locations.


Detect pulse locations using the CLUSTER method


CLUSTER(x, y, data, sd=.07*mean(y), nnadir=2, npeak=3, alpha)


x a vector of observation time points.
y a vector of hormone concentrations.
data a data frame containing the variables occurring in the x and y arguments. If this option is not specified, the variables should be on the search list. Missing values are not allowed.
sd standard deviation for the pooled $t$ test. Default is 7% of the mean response.
nnadir number of nadir points used in the $t$ statistics. Default is 2.
nnpeak number of peak points used in the $t$ statistics. Default is 3.
alpha Significance level of the $t$ statistics.


CLUSTER uses $t$ test between two overlapping consecutive sets of points to identify significant increases and decreases in observations. The default for the standard deviation sd is by no means standard. Users are recommended to provide an accurate estimate instead of using the default.


A vector of pulse locations.


Yu-Chieh Yang, Anna Liu, Yuedong Wang


Veldhuis, J. D. and Johnson, M. L. (1986), Cluster analysis: a simple versatile and robust algorithm for endocrine pulse detection, American Journal of Physiology, 250, E486-E493.

See Also



pl4 <- CLUSTER(time, conc, data=acth, sd=.05*mean(acth$conc), alpha=.2)

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