Chun-Ying Lee [EMAIL PROTECTED] writes:
Hi,
We used known Vm and Km to simulate the data set (time, Cp) without
adding random error in there. Yes, the line looks like very close
to a straight line. But why can't we obtain the correct values with
fitting process? We used optim first
I believe the following is correct:
1.
first of all, as peter daalgaard already pointed out, your data Cp(t)
are following a straight line
very closely, i.e. 0.-order kinetics
2.
for your diff. eq. this means that you are permanently in the range cp
Km so that
dCp/dt = - Vm/Vd = const. =: -b and,
Dear R users:
I encountered difficulties in michaelis-menten equation. I found
that when I use right model definiens, I got wrong Km vlaue,
and I got right Km value when i use wrong model definiens.
The value of Vd and Vmax are correct in these two models.
#-right model
Chun-Ying Lee [EMAIL PROTECTED] writes:
Dear R users:
I encountered difficulties in michaelis-menten equation. I found
that when I use right model definiens, I got wrong Km vlaue,
and I got right Km value when i use wrong model definiens.
The value of Vd and Vmax are correct in these
Chun-Ying Lee wrote:
Dear R users:
I encountered difficulties in michaelis-menten equation. I found
that when I use right model definiens, I got wrong Km vlaue,
and I got right Km value when i use wrong model definiens.
The value of Vd and Vmax are correct in these two models.
Peter Dalgaard [EMAIL PROTECTED] writes:
Chun-Ying Lee [EMAIL PROTECTED] writes:
Dear R users:
I encountered difficulties in michaelis-menten equation. I found
that when I use right model definiens, I got wrong Km vlaue,
and I got right Km value when i use wrong model definiens.
Hi,
We used known Vm and Km to simulate the data set (time, Cp) without
adding random error in there. Yes, the line looks like very close
to a straight line. But why can't we obtain the correct values with
fitting process? We used optim first and then followed by using nls
to fit the model.
