gavinsimpson’s gists

gavinsimpson / predict-bam-bug-with-terms-argument.R

Created May 9, 2022 08:23

Predicting from a model fitted with `bam()` when `discrete = TRUE` was used to both fit and predict from the model with `terms` in the `predict` call doesn't include the model intercept

	# Weird behaviour of predict.bam()

	# packages
	library("mgcv")

	# simulate some data
	set.seed(42)
	df <- gamSim(1, n = 10000)

	# fit a bam with and without discrete = TRUE and a gam

gavinsimpson / smooth_re2.R

Created August 26, 2020 21:07 — forked from noamross/smooth_re2.R

Smooth construct, predict, and plot for random effects with numeric inputs

	#' Create a random effect basis with integers rather than factors
	#' @import mgcv
	#' @export
	smooth.construct.re2.smooth.spec <- function (object, data, knots) {
	if (!is.null(object$id))
	stop("random effects don't work with ids.")
	if(any(sapply(data, is.numeric))) data <- lapply(data, as.factor) ## <-- All I did was this (and below)
	form <- as.formula(paste("~", paste(object$term, collapse = ":"),
	"-1"))
	object$X <- model.matrix(form, data)

gavinsimpson / b-spline-extrapolation.R

Last active October 16, 2023 21:21

Extrapolating with penalised b-splines and mgcv

	## Can we do better extrapolation than the TPRS example used by Gabriel
	## Riutort-Mayol et al in their recent paper on low rank approximations to
	## Gaussian Processes? https://arxiv.org/abs/2004.11408

	## Packages
	library('ggplot2')
	library('tibble')
	library('tidyr')
	library('dplyr')
	library('mgcv')

gavinsimpson / animated-basis-functions.R

Created May 7, 2020 19:18

Animated spline basis functions

	## plots and animations of how basis functions are used to make
	## splines and how these are fitted to data

	library('ggplot2')
	library('tibble')
	library('tidyr')
	library('dplyr')
	library('mgcv')
	library('mvnfast')
	library('purrr')

gavinsimpson / animated-basis-functions.R

Created November 8, 2019 01:36

Animation showing how weighted basis functions combine to yield a cubic regression spline

	## Procuces an animation showing how weighted basis functions combine to produce a sline
	## - this version is for a cubic regression spline basis

	## packages required
	library('ggplot2')
	library('tibble')
	library('tidyr')
	library('dplyr')
	library('mgcv')
	library('mvnfast')

gavinsimpson / maddy-peat.csv

Created June 16, 2018 09:30

peat age data from maddy and drew

Sample	upperDepth	lowerDepth	ageBP	ageError	calUpper	calLower
SRR-4556	20	22	355	35	509	307
SRR-4557	26	28	465	35	542	480
SRR-4558	32	34	635	35	671	545
SRR-4559	38	40	740	35	732	666
SRR-4560	44	46	865	35	916	691
SRR-4561	50	52.5	870	35	918	692
SRR-4562	56	58	985	35	967	795
SRR-4563	100	108	1270	35	1284	1097
SRR-4564	200	207	2575	35	2761	2558

gavinsimpson / darlingtonia.csv

Created June 16, 2018 08:07

Darlingotnia data

We can make this file beautiful and searchable if this error is corrected: Illegal quoting in line 1.

	## leafHeight is in cm.; visited, 1 == TRUE, 0 == FALSE"
	"leafHeight","visited"
	67,1
	84,1
	49,1
	70,1
	77,1
	77,1
	66,1
	65,1

gavinsimpson / data-plus-effects-original-scale.png

Last active February 3, 2021 18:57

Analyse transect data from Shultz et al (2016) PeerJ

gavinsimpson / geochimica-metals.csv

Created October 10, 2017 22:11

Subset of data used in Rose et al (2012) Geochimica et Cosmochimica Acta 82, 113–135 doi: http://doi.org/10.1016/j.gca.2010.12.026

We can make this file beautiful and searchable if this error is corrected: It looks like row 2 should actually have 2 columns, instead of 5 in line 1.

	## Subset of data used in Rose et al (2012) Geochimica et Cosmochimica Acta 82, 113–135 doi: http://doi.org/10.1016/j.gca.2010.12.026
	SiteCode,Date,SoilType,Region,Hg
	CHNA,2000,thin,NW,3.84339855275794
	CHNA,1990,thin,NW,5.42461797827638
	CHNA,1980,thin,NW,8.81972984714937
	CHNA,1970,thin,NW,11.4174572948292
	CHNA,1960,thin,NW,16.513540420367
	CHNA,1950,thin,NW,16.5120469510654
	CHNA,1940,thin,NW,11.1888397621818
	CHNA,1930,thin,NW,11.6222216338607

gavinsimpson / compare-glmmTMB-with-mgcv.R

Last active April 30, 2024 20:09

A quick R script I knocked up to compare the glmmTMB and mgcv packages for fitting zero-inflated GLMMs to the Salamander and Owls data sets from Brooks et al (2017)

	## Compare Brooks et al glmmTMB paper with mgcv

	## Packages
	library("glmmTMB")
	library("mgcv")
	library("ggplot2")
	theme_set(theme_bw())
	library("ggstance")

	## Salamander

Gavin Simpson gavinsimpson