Here is more information on the equation. It is a growth function:
Growth = a + b*(1-exp(-k*time))
where a, b and k are parameters. I wanted to test the difference in total
growth between treatments and the parameters a + b represent total growth.
Thus, I figured that I could add the
On Apr 27, 2011, at 9:28 AM, Schatzi wrote:
Here is more information on the equation. It is a growth function:
Growth = a + b*(1-exp(-k*time))
where a, b and k are parameters. I wanted to test the difference in
total growth between treatments and the parameters a + b represent
total
It is not a human growth curve. The parameter estimates are about:
a = .5
b = 7
k = 1
It is not a sigmoidal curve as there is never a concave segment.
From: ml-node+3478241-1447170361-211...@n4.nabble.com
[mailto:ml-node+3478241-1447170361-211...@n4.nabble.com]
Sent: Wednesday, April 27, 2011
How do I extract the standard error of the parameter estimates?
Also, if I would like to add two parameters together (x+y), can I use this
equation to calculate the new standard error?:
x = parameter 1
y = parameter 2
xSE = SE parameter 1
ySE = SE parameter 2
Hi,
One way would be:
summary(nls.object)[[coefficients]][, Std. Error]
If you have a hankering to do it yourself rather than go through the
summary formula, the code here will get you there:
getAnywhere(summary.nls)
If you are going to be doing it a lot, creating a little function might be
On 2011-04-26 15:11, Joshua Wiley wrote:
Hi,
One way would be:
summary(nls.object)[[coefficients]][, Std. Error]
If you have a hankering to do it yourself rather than go through the
summary formula, the code here will get you there:
getAnywhere(summary.nls)
If you are going to be doing it a
I would generally use the coef() extractor function if
it's available (and it is for nls()). ?nls has an example:
coef(summary(fm1DNase1))
I knew about coef() on model objects, but I did not know it had
methods for their summaries. What wonderful information!
Josh
which is a matrix from
On Tue, Apr 26, 2011 at 2:21 PM, Schatzi adele_thomp...@cargill.com wrote:
How do I extract the standard error of the parameter estimates?
Also, if I would like to add two parameters together (x+y), can I use this
equation to calculate the new standard error?:
x = parameter 1
y = parameter 2
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