On 20/02/2011 18:52, David Winsemius wrote:
On Feb 20, 2011, at 1:27 PM, Ben Ward wrote:
However, the
Y ~ X + Y^2
Produces the best fitting line - it is pretty much on the data points
- I'm trying to make a standard curve, with which to take readings
from a spectrophotometer off of. Rather
On Feb 20, 2011, at 1:27 PM, Ben Ward wrote:
However, the
Y ~ X + Y^2
Produces the best fitting line - it is pretty much on the data
points - I'm trying to make a standard curve, with which to take
readings from a spectrophotometer off of. Rather than what I would
normally use models fo
It is, I tried a glm with a poisson distribution, as was suggested to me
previously, but the Residual Deviance was too high - the book I'm
reading says it suggests overdispersion because it's way above the
Residual degrees of freedom:
glm(formula = Approximate.Counts ~ X..Light.Transmission, f
model <- lm(Approximate.Counts~X..Light.Transmission +
I(Approximate.Counts^2), data=Standards)
Might not be addressing the problem, don't you have Y ~ X + Y^2 here? That's
a violation of the assumptions of an lm isn't it?
Also for plotting CI on a curve look into ggplot2::geom_ribbon, it's muc
Hi David,
I had use log(x)inside the lm call and used predict, although I didn't
know about logs of data making a multiplacative model
exp(log(x)+log(y)) = x*y.
I'll have a look at the poisson model. and see what I manage to produce.
Looking at the internet the Cumulative distribution functio
On Feb 19, 2011, at 1:08 PM, Ben Ward wrote:
Hi Graham,
Thanks, that does explain lots. I've been playing with making log's of
data in models to make the relationship linear, which it does, which
suggests to me that lm() is the right way to go, however, after if
try
to predict after y valu
Hi Graham,
Thanks, that does explain lots. I've been playing with making log's of
data in models to make the relationship linear, which it does, which
suggests to me that lm() is the right way to go, however, after if try
to predict after y values after about 60% on the x axis for light
trans
I've just realised the couple of graphs I put on here have been stripped
off. If anyone has to see them and can't see my problem from code, I can
send them directly to anyone who thinks they can help but wants to see them.
Thanks,
Ben W.
On 18/02/2011 23:29, Ben Ward wrote:
Hi, I wonder if an
Hi, I wonder if anyone could advise me with this:
I've been trying to make a standard curve in R with lm() of some
standards from a spectrophotometer, so as I can express the curve as a
formula, and so obtain values from my treated samples by plugging in
readings into the formula, instead of t
9 matches
Mail list logo
