Slope.Rd
It calculates the slope with linear regression of log(y) ~ x
Slope(x, y)
vector values of the independent variable, usually time
vector values of the dependent variable, usually concentration
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.
R-squared
adjusted R-squared
number of points used for slope
negative of the slope, lambda_z
intercept of the regression line
correlation of log(y) and x
earliest x for lambda_z
last x for lambda_z
Slope(Indometh[Indometh$Subject==1, "time"], Indometh[Indometh$Subject==1, "conc"])
#> R2 R2ADJ LAMZNPT LAMZ b0 CORRXY LAMZLL
#> 0.5340746 0.4823051 11.0000000 0.1332090 0.8108532 -0.7308041 0.2500000
#> LAMZUL
#> 8.0000000