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  "Title": "Code and Data Accompanying the Eco-Stats Text (Warton 2022)",
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  "Description": "Functions and data supporting the Eco-Stats text (Warton,\n2022, Springer), and solutions to exercises. Functions include\ntools for using simulation envelopes in diagnostic plots, and a\nfunction for diagnostic plots of multivariate linear models.\nDatasets mentioned in the package are included here (where not\navailable elsewhere) and there is a vignette for each chapter\nof the text with solutions to exercises.",
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  "Repository": "https://dwarton.r-universe.dev",
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    {
      "source": "Chapter1Solutions.Rmd",
      "filename": "Chapter1Solutions.html",
      "title": "Chapter 1 -- 'STATS 101' Revision -- Exercise solutions and Code Boxes",
      "author": "David Warton",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Exercise 1.1: Experimental design issues",
        "Exercise 1.2: Which plot for which research question?",
        "Exercise 1.3: Raven count data -- what data properties?",
        "Exercise 1.4: Gender ratios in bats",
        "Exercise 1.5: Ravens and gunshots",
        "Exercise 1.6: Pregnancy and smoking",
        "Exercise 1.7: Inference notation -- Gender ratio in bats",
        "Exercise 1.8: Inference notation -- raven counts",
        "Code Box 1.1: Analysing Kerry's sex ratio data on bats",
        "Exercise 1.9: Assumptions -- Gender ratio in bats",
        "Exercise 1.10: Assumptions -- Raven example",
        "Code Box 1.2: Normal quantile plot for the raven data",
        "Code Box 1.3: log(y + 1)-transformation of the raven data",
        "Exercise 1.11: Height and latitude",
        "Exercise 1.12: Transform plant height?",
        "Exercise 1.13: Snails on seaweed",
        "Exercise 1.14: Transform snails?"
      ],
      "created": "2021-03-09 10:36:13",
      "modified": "2022-06-09 04:14:03",
      "commits": 3
    },
    {
      "source": "Chapter10Solutions.Rmd",
      "filename": "Chapter10Solutions.html",
      "title": "Chapter 10 -- Analysing discrete data -- Exercise solutions and Code Boxes",
      "author": "David Warton",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Exercise 10.1: Crabs on seaweed",
        "Exercise 10.2: Do offshore wind farms affect fish communities?",
        "Exercise 10.3: Invertebrate response to bush regeneration}",
        "Code Box 10.1: Example GLM fits for Exercises 10.1-3.}",
        "Code for Fig. 10.5",
        "Code Box 10.2: A summary of a GLM fit to the crab presence-absence data of Exercise 10.1",
        "Code Box 10.3: Dunn-Smyth residual plots for the crab data, using the mvabund package",
        "Code for Figure 10.8",
        "Exercise 10.4: Counts of Ostracods in habitat configuration experiment.",
        "Code Box 10.4: Assumption checking for Ostracod counts of Exercise 10.4.}",
        "Exercise 10.5: Checking the Poisson assumption on the wind farm data.",
        "Exercise 10.6: Checking the Poisson assumption for the worm counts.}\\label",
        "Code Box 10.5: R code using the anova function to test the key hypotheses of interest to David and Alistair in Exercise 10.1.",
        "Exercise 10.7: Testing if there a wind farm effect",
        "Code Box 10.6: Model-based inference for Anthony's worm counts from Exercise 10.3.",
        "Code Box 10.7: Design-based inference for David's and Alistair's crab data using mvabund.",
        "Code Box 10.8: Getting the wrong answer by ignoring overdispersion in Anthony's worm counts from Exercise 10.3.",
        "Code Box 10.9: Using an observation-level random effect for a binomial response",
        "Exercise 10.8: Anthony's ant data.",
        "Exercise 10.9: Worm counts with different numbers of pitfall traps",
        "Code Box 10.10: Adding an offset to the model for worm counts.",
        "Exercise 10.10: Anthony's cockroaches"
      ],
      "created": "2021-03-25 06:56:10",
      "modified": "2022-08-25 02:34:11",
      "commits": 10
    },
    {
      "source": "Chapter11Solutions.Rmd",
      "filename": "Chapter11Solutions.html",
      "title": "Chapter 11 -- Multivariate analysis -- Exercise solutions and Code Boxes",
      "author": "David Warton",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Exercise 11.1: Leaf economics and environment",
        "Exercise 11.2: Flower size and shape",
        "Exercise 11.3: Hunting spiders and their environment",
        "Code Box 11.1: Sample variance-covariance matrices on R",
        "Code Box 11.2: Fitting a multivariate linear model to the leaf economics data.",
        "Code Box 11.3: Checking multivariate linear model assumptions for leaf economics data",
        "Code Box 11.4: A multivariate linear model for the leaf economics data using mvabund",
        "Exercise 11.4: Transforming Ian's leaf economics data",
        "Exercise 11.5: Transforming Edgar's data?",
        "Code Box 11.5: Preparing spider data for analysis on lme4 or glmmTMB",
        "Code Box 11.6: Fitting a hierarchical GLM to spider data on glmmTMB",
        "Code Box 11.7: MCMCglmm fit to Petrus’s spider genus data",
        "Exercise 11.6: Different effects on different spider genera?",
        "Code for Figure 11.4",
        "Code Box 11.8: Diagnostic plots for a hierarchical GLM of Petrus’s spider data",
        "Code Box 11.9: Diagnosing convergence in a MCMCglmm fit",
        "Exercise 11.7: Non-converging model for Petrus’s Alopecosa species"
      ],
      "created": "2022-02-01 04:15:21",
      "modified": "2022-08-25 02:34:11",
      "commits": 7
    },
    {
      "source": "Chapter12Solutions.Rmd",
      "filename": "Chapter12Solutions.html",
      "title": "Chapter 12 -- Visualising many responses -- Exercise solutions and Code Boxes",
      "author": "David Warton",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Exercise 12.1: Flower size and shape",
        "Exercise 12.2: Bush regeneration and invertebrate counts",
        "Code Box 12.1: Plotting the bush regeneration data of Exercise 12.1 using mvabund.",
        "Code Box 12.2: A PCA of Edgar's Iris data",
        "Code Box 12.3: Factor analysis of the Iris data",
        "Code Box 12.4: Assumption checking for a factor analysis of the Iris data",
        "Exercise 12.4: A factor analysis for Anthony’s data(?)",
        "Code Box 12.5: Choosing the number of factors for the iris data",
        "Code Box 12.6: A generalised latent variable model for Anthony’s revegetation data",
        "Exercise 12.5: Checking analysis decisions for Anthony’s revegetation data",
        "Code Box 12.7: A non-metric multi-dimensional scaling ordination of Anthony’s data",
        "Exercise 12.6: MDS ordinations of coral data",
        "Code Box 12.8: Studying each observation separately for the Iris data"
      ],
      "created": "2022-02-01 04:15:21",
      "modified": "2022-08-25 02:34:11",
      "commits": 7
    },
    {
      "source": "Chapter13Solutions.Rmd",
      "filename": "Chapter13Solutions.html",
      "title": "Chapter 13 -- Allometric line-fitting -- Exercise solutions and Code Boxes",
      "author": "David Warton",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Exercise 13.1: Brain size-body size relationships",
        "Exercise 13.2: Leaf economics and environment",
        "Code Box 13.1: Linear models of the brain size-body size data",
        "Code Box 13.2: Testing if the brain-body mass slope is 2/3",
        "Code Box 13.3: Comparing allometric slopes for Ian’s data using smatr",
        "Code Box 13.4: Comparing elevations of allometric lines for Ian’s low soil nutrients data using smatr",
        "Code Box 13.5: Residual plots for brain-body size relationship",
        "Code Box 13.6: Robust SMA for brain-body size relationship",
        "Exercise 13.3: Outlier sensitivity for the brain-body mass data",
        "Exercise 13.4: Robust allometric line fitting for Ian’s leaf data"
      ],
      "created": "2022-02-01 04:15:21",
      "modified": "2022-08-16 04:48:15",
      "commits": 3
    },
    {
      "source": "Chapter14Solutions.Rmd",
      "filename": "Chapter14Solutions.html",
      "title": "Chapter 14 -- Multivariate abundances -- inference about environmental associations -- Exercise solutions and Code Boxes",
      "author": "David Warton",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Exercise 14.1: Revegetation and invertebrate counts",
        "Exercise 14.2: Invertebrates settling on seaweed",
        "Exercise 14.3: Do offshore wind farms affect fish communities?",
        "Code Box 14.1: Using mvabund to test for an effect of revegetation in Exercise 12.2",
        "Exercise 14.4: Testing for an effect of isolation on invertebrates in seaweed",
        "Code Box 14.2: Checking assumptions for the revegetation model of Code Box 14.1",
        "Code Box 14.3: Checking mean-variance assumptions for a Poisson revegetation model",
        "Exercise 14.5: Checking assumptions for the habitat configuration data",
        "Exercise 14.6: Checking assumptions for the wind farm data",
        "Code Box 14.4: A manyglm analysis of the revegetation data, using a statistic accounting for correlation",
        "Exercise 14.7: Testing for an effect of offshore wind farms (slowly)",
        "Code Box 14.5: Analysing ordinal data from the habitat configuration study using manyany",
        "Code Box 14.6: A compositional analysis of Anthony’s revegetation",
        "Code Box 14.7: A faster compositional analysis of Anthony’s revegetation data",
        "Code Box 14.8: Quick-and-dirty compositional analysis of Anthony’s revegetation data",
        "Code Box 14.9: Posthoc testing for the bush regeneration data",
        "Code Box 14.10: Exploring indicator taxa most strongly associated with the treatment effect in Anthony’s revegetation data",
        "Exercise 14.8: Indicator species for offshore wind farms?"
      ],
      "created": "2022-02-01 04:15:21",
      "modified": "2022-08-25 02:34:11",
      "commits": 10
    },
    {
      "source": "Chapter15Solutions.Rmd",
      "filename": "Chapter15Solutions.html",
      "title": "Chapter 15 -- Predicting multivariate abundances -- Exercise solutions and Code Boxes",
      "author": "David Warton",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Exercise 15.1: Predicting fish communities at wind farms?",
        "Exercise 15.2: Which environmental variables predict hunting spider communities?",
        "Code Box 15.1: Predictive likelihood for the wind farm data",
        "Exercise 15.3: Cross-validation for wind farm data and rare species",
        "Code Box 15.2: Fitting a mixed model to the wind farm data",
        "Exercise 15.4: Predictive likelihood for wind farm mixed model",
        "Code Box 15.3: Fitting a LASSO to the wind farm data via glmnet",
        "Code Box 15.4: Fitting a group-LASSO to the wind farm data",
        "Exercise 15.5: Comparing predictive likelihoods for the wind farm data",
        "Code Box 15.5: Reduced rank regression for the wind farm data",
        "Code Box 15.6: Using the LASSO for Petrus’s spider data",
        "Code Box 15.7: Mixed model prediction of spider abundances"
      ],
      "created": "2022-02-01 04:15:21",
      "modified": "2022-08-25 02:34:11",
      "commits": 7
    },
    {
      "source": "Chapter16Solutions.Rmd",
      "filename": "Chapter16Solutions.html",
      "title": "Chapter 16 -- Understanding variation in environmental response across taxa -- Exercise solutions and Code Boxes",
      "author": "David Warton",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Exercise 16.1: Understanding how spiders vary in environmental response",
        "Code Box 16.1: Fitting a Species Archetype Model to Petrus’s spider data",
        "Code Box 16.2: Minding your P’s and Q’s for Petrus’s Species Archetype Model",
        "Exercise 16.2: Archetypal revegetation response",
        "Code Box 16.3: Choosing the number of archetypes for Petrus’s spider data",
        "Exercise 16.3: How many revegetation archetypes?",
        "Exercise 16.4: Understanding why spiders vary in environmental response",
        "Code Box 16.4: A fourth corner model for spider data using traitglm",
        "Exercise 16.5: Heloise’s ants",
        "Code Box 16.5: A fourth corner interaction plot for Petrus’s spider data",
        "Exercise 16.6: A fourth corner interaction plot for Heloise’s ants",
        "Code Box 16.6: Quantifying how effectively traits explain 𝛽-diversity",
        "Exercise 16.7: Variation explained by traits for Heloise’s ants"
      ],
      "created": "2022-02-01 04:15:21",
      "modified": "2022-08-25 02:34:11",
      "commits": 10
    },
    {
      "source": "Chapter17Solutions.Rmd",
      "filename": "Chapter17Solutions.html",
      "title": "Chapter 17 -- Studying co-occurrence patterns -- Exercise solutions and Code Boxes",
      "author": "David Warton",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Exercise 17.1: Co-occurrence in hunting spider data",
        "Code Box 17.1: Estimating co-occurrence patterns using a copula model",
        "Code Box 17.2: Co-occurrence patterns explained by environmental variables",
        "Exercise 17.2: Spider presence-absence",
        "Exercise 17.3: Co-occurrence in bird communities",
        "Code Box 17.3: A copula graphical model for Petrus’s spider data",
        "Exercise 17.4: Does soil dryness explain co-occurrence patterns in Petrus’s data?"
      ],
      "created": "2022-02-01 04:15:21",
      "modified": "2022-05-06 00:21:31",
      "commits": 3
    },
    {
      "source": "Chapter2Solutions.Rmd",
      "filename": "Chapter2Solutions.html",
      "title": "Chapter 2 -- An importance equivalence result -- Exercise solutions and Code Boxes",
      "author": "David Warton",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Exercise 2.1 Two-sample t-test for guinea pig experiment",
        "Code Box 2.1 A two-sample t-test of the data from the guinea pig experiment",
        "Code Box 2.2: Smoking and pregnancy -- checking assumptions",
        "Exercise 2.2: Water quality",
        "Code Box 2.3: Fitting a linear regression to the water quality data",
        "Exercise 2.3: Water quality -- interpreting R output",
        "Code Box 2.4: Diagnostic plots for the water quality data",
        "Exercise 2.4: Water quality{ assumption checks",
        "Code Box 2.5: Two-sample t-test output for the smoking-pregnant data, again",
        "Code Box 2.6: Linear regression analysis of the smoking-pregnant data. compare to Code Box 2.5",
        "Exercise 2.5: Global plant height against latitude",
        "Exercise 2.6: Transform guinea pigs?",
        "Exercise 2.7: Influential value in the water quality data"
      ],
      "created": "2021-03-09 10:36:13",
      "modified": "2022-05-06 00:21:31",
      "commits": 4
    },
    {
      "source": "Chapter3Solutions.Rmd",
      "filename": "Chapter3Solutions.html",
      "title": "Chapter 3 -- Regression with multiple predictor variables -- Exercise solutions and Code Boxes",
      "author": "David Warton",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Exercise 3.1: Global plant height",
        "Code Box 3.1: Simple linear regression of global plant height data - predicting",
        "Code Box 3.2: Multiple linear regression of global plant height data on R -- predicting",
        "Code Box 3.3: R code to produce the plots of Figure 3.1",
        "Code Box 3.4: Tests of multiple parameters on R using the anova function",
        "Code Box 3.5: Multi-collinearity example -- adding rainfall in the wettest month (rain.wetm) to a model that already has annual precipitation (rain).",
        "Exercise 3.2: Plant height data -- transform response?",
        "Exercise 3.3: Plant height -- skewed rainfall data?",
        "Code Box 3.6: Computing variance inflation factors to check for multi-collinearity.",
        "Code Box 3.7: Correlations and pairwise scatterplots to look for multi-collinearity.",
        "Exercise 3.4: Snails on seaweed",
        "Code Box 3.8: Analysis of variance in R for the seaweed data of Exercise 1.13 using",
        "Code Box 3.9: Running confint on the seaweed data doesn't give us what we",
        "Code Box 3.10: Analysis of variance of the seaweed data of Exercise 1.13 with Tukey's multiple comparisons via the multcomp package.",
        "Exercise 3.5: Plant height -- climate explains patterns?",
        "Exercise 3.6: Habitat con�guration study { mind your P's and Q's",
        "Exercise 3.7: Habitat con�guration study { small plots"
      ],
      "created": "2021-03-09 10:36:13",
      "modified": "2022-08-25 02:34:11",
      "commits": 7
    },
    {
      "source": "Chapter4Solutions.Rmd",
      "filename": "Chapter4Solutions.html",
      "title": "Chapter 4 -- Linear models -- anything goes -- Exercise solutions and Code Boxes",
      "author": "David Warton",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Exercise 4.1: Ravens and gunshots",
        "Code Box 4.1: Paired t-test for the ravens data",
        "Exercise 4.2: Ravens, guns and air horns",
        "Code Box 4.2: Paired t-test for the ravens data via a linear model",
        "Code Box 4.3: A linear model for the blocked design given by the raven counts in Exercise 4.2",
        "Exercise 4.3: Seaweed, snails and seaweed mass",
        "Code Box 4.4: Scatterplot of data from Exercise 4.3.",
        "Code Box 4.5: Analysis of covariance for the seaweed data of Exercise 4.3.",
        "Exercise 4.4: Checking ANCOVA assumptions",
        "Code Box 4.6: ANCOVA with the order of terms switched.",
        "Exercise 4.5: Order of terms in writing out a model for snails and seaweed.",
        "Code Box 4.7: \"Type II sums of squares\" for the ANCOVA of snails and seaweed.",
        "Exercise 4.6: Snails, isolation and time",
        "Code Box 4.8: A comparative boxplot of snail density at each of the six possible combinations of sampling time and distance of isolation.",
        "Exercise 4.7: Factorial ANOVA assumptions",
        "Code Box 4.9: Factorial ANOVA of Snails, Isolation, and Time",
        "Code Box 4.10: R code for the interaction plot in Figure 4.1.",
        "Code Box 4.11: Uh oh... anova gone wrong",
        "Code Box 4.12: Tukey's comparisons don't work for main e�ects in an orthogonal design, as seen for Exercise 4.9:",
        "Code Box 4.13: Tukey's comparisons for a main e�ect of Dist for Exercise 4.6, assuming no interaction.",
        "Code Box 4.14: Tukey's comparisons for all possible treatment combinations for Exercise 4.6.",
        "Code Box 4.15: Tukey's comparisons for Dist within each sampling time, for Exercise 4.6.",
        "Code Box 4.16: Testing for an interaction in an ANCOVA for density of epifauna as a function of Dist and algal wet mass.",
        "Exercise 4.8: Global plant height",
        "Code Box 4.17: Using R to fit a quadratic model to the plant height data of Exercise 3.1.",
        "Exercise 4.9: Snowmelt and time to flowering",
        "Exercise 4.10: Bird exclusion and biological control",
        "Exercise 4.11: Seaweed, snails and three factors"
      ],
      "created": "2021-03-09 10:36:13",
      "modified": "2022-08-25 02:34:11",
      "commits": 6
    },
    {
      "source": "Chapter5Solutions.Rmd",
      "filename": "Chapter5Solutions.html",
      "title": "Chapter 5 -- Model selection -- Exercise solutions and Code Boxes",
      "author": "David Warton",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Exercise 5.1: Plant height and climate",
        "Figures 5.1-5.2: bias-variance trade-off for polynomial models",
        "Code Box 5.1: Using validation for model selection using Angela's plant height data",
        "Code Box 5.2: 5-fold cross-validation for the data of Exercise 5.1",
        "Code Box 5.3: Computing Information Criteria on R for Exercise 5.1",
        "Code Box 5.4: All subsets selection for the plant height data of 5.1",
        "Code Box 5.5: Stepwise subset selection for the plant height data of 5.1",
        "Simulation code for Figure 5.4",
        "Code Box 5.6: LASSO for plant height data of 5.1",
        "Exercise 5.2: Relative importance of climate variables",
        "Code Box 5.7: Sequential $R^2$ for variable importance",
        "Code Box 5.8: Marginal and conditional $R^2$ for variable importance",
        "Code Box 5.9: Standardised coefficients for Angela's height data",
        "Exercise 5.3: Variable importance output",
        "Code Box 5.10: Importance of temperature vs rainfall",
        "Code for Figure 5.5",
        "Exercise 5.4: Head bobs in lizards -- do their displays change with the environment?",
        "Exercise 5.5 Plant height data and precipitation"
      ],
      "created": "2021-03-09 10:36:13",
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      "source": "Chapter6Solutions.Rmd",
      "filename": "Chapter6Solutions.html",
      "title": "Chapter 6 -- Mixed effect models -- Exercise solutions and Code Boxes",
      "author": "David Warton",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Exercise 6.1: Effects of water pollution on subtidal marine micro-invertebrates",
        "code for Fig 6.1",
        "Code Box 6.1: Fitting a linear mixed model to the estuary data of Exercise 6.1",
        "Code Box 6.2: Residual plots from a mixed model for Exercise 6.1",
        "Code Box 6.3: Using anova to compare mixed effects models for the estuary data",
        "Code Box 6.4: Confidence intervals for parameters from a mixed effects model for the estuary data",
        "Code Box 6.5: Prediction intervals for random effects terms in a mixed effects model",
        "Exercise 6.2: Fitting random effects with different variances",
        "Exercise 6.3: Bird exclusion and biological control",
        "Exercise 6.4: Estuary data in different zones",
        "Code Box 6.6: Using the parametric bootstrap to compute the standard error of the Mod fixed effect in Exercise 6.1.",
        "Code Box 6.7: A parametric bootstrap to test for an effect of Estuary in Exercise 6.1.",
        "Exercise 6.6: Accurate inferences about the estuary data"
      ],
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      "modified": "2022-06-09 04:14:03",
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      "source": "Chapter7Solutions.Rmd",
      "filename": "Chapter7Solutions.html",
      "title": "Chapter 7 -- Correlated samples in times, space, phylogeny... -- Exercise solutions and Code Boxes",
      "author": "David Warton",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Exercise 7.1: Biological control of aphids over time",
        "Code Box 7.1: R code to produce Figure 7.2.",
        "Code Box 7.2: Choosing a longitudinal model for the aphid data",
        "Code Box 7.3: Exploring the random intercept fit to the aphids data",
        "Code Box 7.4: Exploring the random slopes fit to the aphids data",
        "Exercise 7.2: Biological control of aphids in a wheat field",
        "Exercise 7.3: Biological control of aphids across both fields!",
        "Exercise 7.4: Eucalypt richness as a function of the environment",
        "Code Box 7.5: Model selection to choose predictors, and a spatial model, for Ian's richness data",
        "Code Box 7.6: Inferences from spatial and non-spatial models for Ian's richness data",
        "Code Box 7.7: Spatial correlogram for Ian's species richness data",
        "Exercise 7.5: Egg size when Dads incubate",
        "Code Box 7.8: Phylogenetic tree of 71 shorebird species",
        "Code Box 7.9: Exploratory analysis of egg size data}\\label",
        "Code Box 7.10: Comparative analysis of egg size data",
        "Code Box 7.11: Residual diagnostics for egg size data",
        "Exercise 7.6: Comparative analysis of egg size data revisited"
      ],
      "created": "2021-03-12 00:40:31",
      "modified": "2022-08-25 02:34:11",
      "commits": 8
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    {
      "source": "Chapter8Solutions.Rmd",
      "filename": "Chapter8Solutions.html",
      "title": "Chapter 8 -- Wiggly Models -- Exercise solutions and Code Boxes",
      "author": "David Warton",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Code Box 8.1: Fitting a spline smoother to the Mauna Loa annual data of Exercise 8.1 on R.",
        "Code Box 8.2: Residual plot from a GAM of the annual Mauna Loa data of Exercise 8.1",
        "Code Box 8.3: Comparing curves for the Mauna Loa data.",
        "Exercise 8.2: Eucalypt richness as a function of the environment",
        "Code Box 8.4: Handling interactions in a GAM, when modelling Ian's richness data as a function of minimum temperature and rainfall, for Exercise 8.2",
        "Exercise 8.3: Smoothers for climate effects on plant height",
        "Code Box 8.5: Residual plot with a smoother to diagnose a model.",
        "Exercise 8.4: Nonlinear predictors of species richness?",
        "Exercise 8.5: Carbon dioxide measurements at Mauna Loa observatory",
        "Code Box 8.6: A simple model for the Mauna Loa monthly data with a cyclical predictor",
        "Code Box 8.7: Residual plots across time and season for the Mauna Loa monthly data",
        "Code Box 8.8: Another model for the Mauna Loa monthly data, with an extra sine curve in there to better handle irregularities in the seasonal effect}\\label",
        "Code Box 8.9: Mauna Loa model with autocorrelation}\\label",
        "Exercise 8.6: Mauna Loa monthly data -- an extra term in seasonal trend?",
        "Exercise 8.7: Mauna Loa annual data -- temporal autocorrelation?}",
        "Exercise 8.8: Aspect as a predictor of species richness"
      ],
      "created": "2021-03-12 00:40:31",
      "modified": "2022-06-09 04:14:03",
      "commits": 7
    },
    {
      "source": "Chapter9Solutions.Rmd",
      "filename": "Chapter9Solutions.html",
      "title": "Chapter 9 -- Design-based inference -- Exercise solutions and Code Boxes",
      "author": "David Warton",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Exercise 9.1: Smoking in pregnancy",
        "Exercise 9.2: Three example permutations of treatment labels in the guinea pig data",
        "Code behind Figure 9.1",
        "Code Box 9.1: A permutation test for the guinea pig data using mvabund",
        "Code Box 9.2: Permutation test for a relationship between latitude and plant height",
        "Code Box 9.3: Using the mvabund package for a bootstrap test of guinea pig data",
        "Exercise 9.3: Case resampling in the guinea pig data",
        "Exercise 9.4: Global plant height -- does rainfall explain latitude effect?",
        "Code Box 9.4: Residual resampling using mvabund for Exercise 9.4.",
        "Code Box 9.5: Plant height data -- checking assumptions",
        "Exercise 9.5: Plant height data -- log transformation",
        "Exercise 9.6: Guinea pig data -- log transformation",
        "Exercise 9.7: Revisiting linear models past",
        "Repeating Exercise 4.9:",
        "Now repeating Exercise 4.10:",
        "Code Box 9.6: Block resampling using mvabund for estuary data",
        "Code Box 9.7: Block resampling using permute for raven data",
        "Code Box 9.8: Moving block bootstrap test for species richness modelling",
        "Code Box 9.9: Moving block bootstrap standard errors for species richness predictions",
        "Exercise 9.8: Does block length matter?"
      ],
      "created": "2021-03-22 00:18:56",
      "modified": "2022-08-25 02:34:11",
      "commits": 6
    },
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      "source": "ecostats.Rmd",
      "filename": "ecostats.html",
      "title": "Eco-Stats -- Code and Data Accompanying the Eco-Stats Text",
      "author": "David Warton",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Simulation envelopes in plots",
        "anova tests using a parametric bootstrap",
        "Datasets"
      ],
      "created": "2022-08-16 04:48:15",
      "modified": "2022-08-16 04:48:15",
      "commits": 1
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