
It calculates the slope with linear regression of log(y) ~ x
Slope(x, y)
vector values of independent variable, usually time
vector values of dependent variable, usually concentration
R-squared
adjusted R-squared
number of points used for slope
negative of slope, lambda_z
intercept of regression line
correlation of log(y) and x
earliest x for lambda_z
last x for lambda_z
predicted y value at last point, predicted concentration for the last time point
With time-concentration curve, you frequently need to estimate slope in log(concentration) ~ time.
This function is usually called by BestSlope
function and you seldom need to call this function directly.
# NOT RUN {
Slope(Indometh[Indometh$Subject==1, "time"], Indometh[Indometh$Subject==1, "conc"])
# }
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