Displaying 3 results from an estimated 3 matches for "probex".
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probe
2007 Aug 23
0
weighted nls and confidence intervals
for unweighted fits using `nls' I compute confidence intervals for the
fitted model function by using:
#-------------------
se.fit <- sqrt(apply(rr$m$gradient(), 1, function(x) sum(vcov(rr)*outer(x,x))))
luconf <- yfit + outer(se.fit, qnorm(c(probex, 1 - probex)))
#-------------------
where `rr' contains an `nls' object, `x' is the independent variable vector,
`yfit' the corresponding model prediction (`fitted(rr)'), `se.fit' the
corresponding standard error and `luconf' the lower and upper confidence
limits at som...
2007 Aug 31
0
non-linear fitting (nls) and confidence limits
...tings
joerg
original post:
--------------
for unweighted fits using `nls' I compute confidence intervals for the
fitted model function by using:
#-------------------
se.fit <- sqrt(apply(rr$m$gradient(), 1, function(x) sum(vcov(rr)*outer(x,x))))
luconf <- yfit + outer(se.fit, qnorm(c(probex, 1 - probex)))
#-------------------
where `rr' contains an `nls' object, `x' is the independent variable vector,
`yfit' the corresponding model prediction (`fitted(rr)'), `se.fit' the
corresponding standard error and `luconf' the lower and upper confidence
limits at som...
2007 Sep 25
0
non-linear fitting (nls) and confidence limits
...ere,
hoping for some clarifications...):
for _unweighted_ fits using `nls' one can compute confidence intervals for the
fitted model function via
#-------------------
se.fit <- sqrt(apply(res$m$gradient(), 1, function(x) sum(vcov(res)*outer(x,x))))
luconf <- yfit + outer(se.fit, qnorm(c(probex, 1 - probex)))
#-------------------
where `res' contains an `nls' object, `x' is the independent variable vector,
`yfit' the corresponding model prediction (`fitted(res)'), `se.fit' the
corresponding standard error and `luconf' the lower and upper confidence
limits at s...