10,736 reputation
13063
bio website fromthebottomoftheheap.net
location Regina, Canada
age 37
visits member for 4 years, 1 month
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I'm Quantitative Environmental Scientist in the Institute of Environmental Change & Society, at the University of Regina, Canada. I undertake research on environmental problems, including climate change and atmospheric pollution, affecting lakes. I use lake sediments to look back in time at the history of lakes to look at what organisms are present and how the species in the lake have changed through time and how lakes evolve and respond to pollution and perturbations.

I'm also an Adjunct Professor in the Department of Biology at the University of Regina.


1d
comment Likelihood ratio test in R
@Kerry fm1 has a lower log likelihood and hence a poorer fit than fm2. The LRT is telling us that the degree to which we made fm1 a poorer model than fm2 is unexpectedly large if the terms that are different between the models were useful (explained the response). lrtest(fm2) isn't compared with fm1 at all, the model fm2 is compared with in that case if, as stated in the output, this: con ~ 1. That model, the null model, says that the best predictor of con is the sample mean of con (the intercept/constant term).
1d
awarded  Nice Answer
Oct
23
revised Why does this logistic GAM fit so poorly?
More certain...
Oct
23
answered Why does this logistic GAM fit so poorly?
Sep
30
awarded  Explainer
Sep
23
comment What does “independent observations” mean?
No, you can render the residuals independent (or at least reduce dependency to such an extent that the residuals appear independent). This comes say from the assumptions of the linear model; $\varepsilon \sim N(0, \sigma^2 \Lambda)$ where $\Lambda$ is a correlation matrix. The usual assumption is that $\Lambda$ is an identity matrix, hence off-diagonals are zero and hence the assumption of independence is on the residuals. Put another way though, this is a statement about $y$ conditional upon the fitted model.
Sep
23
awarded  Enlightened
Sep
23
awarded  Nice Answer
Sep
22
comment What does “independent observations” mean?
I would also add that choosing appropriate covariates is important here. If gender is a catch-all but not a useful covariate for an effect, collect a better covariate.
Sep
22
comment What does “independent observations” mean?
It must surely depend on the response. If we were looking at grades of students in the sciences in the UK, perhaps there would be an effect with different attainment distributions for the two genders, on average over the populations you are studying. Anyway, all of this only matters (in a statistical model) for the residuals, or put differently for the responses conditional upon the fitted model. In other words, if observations aren't independent, that's OK as long as the model accounts for this such that the residuals are independent.
Sep
22
comment What does “independent observations” mean?
One might suggest that the distribution of grades for teacher 1 had a lower "mean" value than for teacher 2 and hence the students of teacher 1 would all tend to have lower grades, on average, than the students of teacher 2. In other words, the distribution of students/grades for the two teachers could well be different distributions. That would be sufficient to render the observations dependent.
Sep
21
awarded  Yearling
Sep
21
answered Smoothing parameter for spline curve with duplicate points
Sep
16
awarded  Enlightened
Sep
16
awarded  Nice Answer
Aug
25
comment Sum to Zero Constraint GAM Factor Interaction
Read section 4.3 in Simon's book (p169-170). It discusses the sum-to-zero constraint and explicitly references the model matrix, not the "terms" component. The constraint is $\mathbf{1^{T}\tilde{X}_j\tilde{\beta}_j} = 0$ and some re-parameterisation is done to absorb this constraint into the model matrix. So when looking at this you need to include the model matrix and the coefficient vector. But I am struggling to get the correct bits out of mod2 to illustrate this. You may want to email Simon again and post an Answer here if he replies (or ask him if he wants to do it himself?).
Aug
25
comment Sum to Zero Constraint GAM Factor Interaction
Will add a fuller answer tomorrow when i recall the details, but the missing info in your by smoother is that you need to add fac as a fixed effects term to the model as well as the by variable. I will guess that adding that will improve things.
Aug
21
awarded  Nice Answer
Aug
14
comment Introductory Text for GAM
@patrick I assumed this would be closed as not having one or just a couple of answers
Aug
11
answered Testing slopes in multivariate adaptive regression splines (MARS/earth)