How to access values returned by R functions (to put into vectors)?

The question is general for all functions, but here is a specific example -



# For the logistic regression of the following correlated variables:

C <- c(457,   1371,   4113,  12339,  37017, 111051, 333153, 999459)

E <- c(0.003858377, 0.014334578, 0.014092836, 0.737950754, 0.996371828,
0.997482379, 1.005569257, 0.994382856)



#  The nls function:

A = nls(E~(Em*C^p)/(C50^p + C^p), start = list(Em=0.8, p=3, C50=1e3))



# Returns the following parameter estimates for Em, p and C50:

Nonlinear regression model

 model:  E ~ (Em * C^p)/(C50^p + C^p)

  data:  parent.frame()

         Em            p          C50

  0.9989113    4.7957189 9934.6481397

 residual sum-of-squares:  0.0002856567



How do I access these parameter values from this output/function so that it
would go into a vector c(Em,p,C50)?


       [[alternative HTML version deleted]]

The question is general for all functions, but here is a specific example -



# For the logistic regression of the following correlated variables:

C <- c(457,   1371,   4113,  12339,  37017, 111051, 333153, 999459)

E <- c(0.003858377, 0.014334578, 0.014092836, 0.737950754, 0.996371828,
0.997482379, 1.005569257, 0.994382856)



#  The nls function:

A = nls(E~(Em*C^p)/(C50^p + C^p), start = list(Em=0.8, p=3, C50=1e3))



# Returns the following parameter estimates for Em, p and C50:

Nonlinear regression model

  model:  E ~ (Em * C^p)/(C50^p + C^p)

   data:  parent.frame()

          Em            p          C50

   0.9989113    4.7957189 9934.6481397

 residual sum-of-squares:  0.0002856567



How do I access these parameter values from this output/function so that it
would go into a vector c(Em,p,C50)?


        [[alternative HTML version deleted]]