Description Usage Arguments Value
Attempts to fit a single sigmoid to given expression data using expectation maximization.
1 | impulse.fit.single(x, y, k = 20, maxiter = 200, interpolate = NULL)
|
x |
(Numeric) Expression data |
y |
(Numeric) Expression data |
k |
(Numeric) Number of starting conditions to try |
maxiter |
(Numeric) Maximum number of iterations to try fitting |
interpolate |
(Numeric or NULL) If low number of data points, can interpolate them linearly to this number of points for choosing potential starting conditions. Default ( |
(Named vector, length 5) Returns the coefficients and sum of squared residuals of the best fitting double sigmoid out of k
conditions. If all attempts to fit fail to converge, returns vector of same length, with all values NA
.
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