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  "Description": "Maximum likelihood estimation of landscape conductance\nsurfaces from genetic data on raster graphs, using Newton and\nquasi-Newton optimization with analytic derivatives. Fits\nlog-linear conductance models with optional joint estimation of\nGaussian smoothing scales and spline response shapes, linked to\npairwise genetic distances through maximum likelihood\npopulation effects models or to allele-frequency covariance\nthrough a Wishart likelihood on site contrasts, with the same\npairwise distance and environment covariates available in both.\nProvides exact sparse and iterative solvers for large rasters,\nfixed-domain spatial cross-validation for comparing conductance\nformulas, and simulation tools for study design. Works with\n'terra' objects. Fitting one parameterized conductance surface\nto genetic data, rather than regressing on separate resistance\ndistances, follows Peterman and Pope (2021)\n<doi:10.1111/mec.15716>. Background on population-effects\nmodels and circuit-based covariance models is provided by\nClarke, Rothery and Raybould (2002) <doi:10.1198/108571102320>\nand Hanks and Hooten (2013) <doi:10.1080/01621459.2012.724647>,\nrespectively.",
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      "page": "aic_table",
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      "page": "ArmijoControl",
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    {
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      "title": "Gaussian scale-aware log-linear conductance model",
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    {
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    {
      "page": "ohio_ponds",
      "title": "Simulated Ohio Forest-Pond Genetic Data",
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    {
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      "title": "Conductance model factories",
      "topics": [
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      "page": "terradish_cv_folds",
      "title": "Fixed-domain cross-validation for terradish models",
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    {
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      "title": "Resistance distances from a parameterized conductance surface",
      "topics": [
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      "title": "Construct reproducible cross-validation folds",
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      "page": "terradish_grid",
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      "page": "terradish_ibe_ratio",
      "title": "Environmental effects in resistance-distance units",
      "topics": [
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      "title": "Wishart covariance measurement model",
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      "title": "Wishart measurement models with site-level environmental covariance kernels",
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    {
      "source": "categorical-conductance.Rmd",
      "filename": "categorical-conductance.html",
      "title": "Categorical Landscape Covariates",
      "author": "Bill Peterman",
      "engine": "knitr::rmarkdown",
      "headings": [
        "What does a categorical coefficient mean?",
        "Load a factor-valued raster",
        "Specify the reference and contrasts",
        "Generate a specified covariance example",
        "Fit and interpret the class contrast",
        "Plot a class contrast and its map",
        "Verify what changing the reference does",
        "Evaluate class and continuous candidates on the same folds",
        "Smoothing land-cover classes",
        "Quick reference: a categorical conductance workflow",
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    {
      "source": "wishart-covariance.Rmd",
      "filename": "wishart-covariance.html",
      "title": "Choosing and Checking a Genetic Covariance Response",
      "author": "Bill Peterman",
      "engine": "knitr::rmarkdown",
      "headings": [
        "What genetic quantity are you modeling?",
        "Preserve sampling order and marker meaning",
        "Check covariance and distance geometry",
        "Inspect the response as a matrix",
        "Separate marker count from assumed information",
        "Adapt the construction to your data",
        "Summary of key functions",
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      "modified": "2026-10-28 18:31:49",
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    {
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      "filename": "gaussian-scale-optimization.html",
      "title": "Gaussian Scale Optimization",
      "author": "Bill Peterman",
      "engine": "knitr::rmarkdown",
      "headings": [
        "What question does a Gaussian scale answer?",
        "Rebuild the shared response and graph",
        "Set interpretable scale bounds and fit",
        "Inspect scale uncertainty with a likelihood profile",
        "View conductance at the fitted scale",
        "Compare estimated and fixed context",
        "Evaluate prediction in whole held-out ponds",
        "What to take to your own study",
        "Quick reference: estimate and validate one Gaussian context",
        "Summary of key functions",
        "See also"
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      "created": "2026-04-09 11:49:46",
      "modified": "2026-10-28 18:31:49",
      "commits": 17
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    {
      "source": "getting-started.Rmd",
      "filename": "getting-started.html",
      "title": "Getting Started with terradish",
      "author": "Bill Peterman",
      "engine": "knitr::rmarkdown",
      "headings": [
        "What will you learn?",
        "Choose your next question",
        "Meet the forest-pond example",
        "Load and inspect the data",
        "Turn SNP dosage into a pond covariance",
        "Build the conductance graph",
        "Fit forest and uniform-conductance models",
        "Check convergence, comparison, and adequacy",
        "Follow forest from conductance to the genetic response",
        "Construct the matched microsatellite response",
        "Quick reference: a complete fixed-context SNP workflow",
        "Summary of key functions",
        "See also"
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      "created": "2026-04-03 00:47:39",
      "modified": "2026-10-28 18:31:49",
      "commits": 28
    },
    {
      "source": "data-generation.Rmd",
      "filename": "data-generation.html",
      "title": "How the Salamander Example Data Were Generated",
      "author": "Bill Peterman",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Two examples, three kinds of data",
        "Prepare the real landscape",
        "Generate the pond history in SLiM",
        "Generate the terrestrial history in SLiM",
        "Select animals before examining genotypes",
        "Add ancestry and matched markers",
        "From genotypes to the modeled response",
        "Reproduce an analysis or regenerate a history",
        "See also",
        "Reference"
      ],
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      "modified": "2026-10-28 18:31:49",
      "commits": 1
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    {
      "source": "individual-salamanders.Rmd",
      "filename": "individual-salamanders.html",
      "title": "Individual genotypes and nonlinear landscape resistance",
      "author": "Bill Peterman",
      "engine": "knitr::rmarkdown",
      "headings": [
        "What you will learn",
        "Load the matched example",
        "The landscape, animals, and sampling",
        "From individual genotypes to a covariance response",
        "Why not use the biallelic helpers here?",
        "Build a nonlinear drying model",
        "Test prediction before calling this IBR recovery",
        "A separate genomic assay with no parameter refitting",
        "Keep IBE distinct from IBR",
        "Scope of this dataset",
        "Quick reference",
        "Reference"
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      "created": "2026-10-28 18:31:49",
      "modified": "2026-10-28 18:31:49",
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    {
      "source": "ibe-ibr-workflow.Rmd",
      "filename": "ibe-ibr-workflow.html",
      "title": "Isolation by Environment and Resistance",
      "author": "Bill Peterman",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Three environmental hypotheses that should stay distinct",
        "Prepare the graph, genotypes, and endpoint differences",
        "Define the two measurement constructions",
        "This kernel is not a Gaussian similarity kernel",
        "Use the SLiM SNP response as a negative control",
        "A separate positive example: generate a covariance component",
        "Plot the environmental contribution",
        "Validate an environmental extension within one family",
        "Interpreting IBE in field data",
        "Quick reference: SNP negative-control construction",
        "Summary of key functions",
        "See also"
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      "created": "2026-04-01 21:33:45",
      "modified": "2026-10-28 18:31:49",
      "commits": 21
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    {
      "source": "large-landscapes.Rmd",
      "filename": "large-landscapes.html",
      "title": "Large Landscapes",
      "author": "Bill Peterman",
      "engine": "knitr::rmarkdown",
      "headings": [
        "When a landscape is \"large\"",
        "Choosing a solver",
        "Reusing Windows workers",
        "Controlling the nuisance profile",
        "Curvature for standard errors",
        "Information and effective degrees of freedom",
        "Cropping and coarse warm starts",
        "Storing large fitted objects",
        "Quick reference",
        "Summary of key functions",
        "See also"
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      "created": "2026-06-15 23:22:33",
      "modified": "2026-10-28 18:31:49",
      "commits": 7
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    {
      "source": "model-comparison.Rmd",
      "filename": "model-comparison.html",
      "title": "Model Comparison and Selection in terradish",
      "author": "Bill Peterman",
      "engine": "knitr::rmarkdown",
      "headings": [
        "What evidence should choose a model?",
        "Prepare one response and one landscape",
        "Declare the biological candidates",
        "Read information criteria with their assumptions",
        "Use a likelihood-ratio test only for a nested question",
        "Inspect conditional associations",
        "Compare spatial prediction",
        "Put the evidence together",
        "Quick reference: a complete candidate comparison",
        "Summary of key functions",
        "See also"
      ],
      "created": "2026-04-03 00:47:39",
      "modified": "2026-10-28 18:31:49",
      "commits": 21
    },
    {
      "source": "mlpe-pairwise-distance.Rmd",
      "filename": "mlpe-pairwise-distance.html",
      "title": "Pairwise Genetic Distances with MLPE",
      "author": "Bill Peterman",
      "engine": "knitr::rmarkdown",
      "headings": [
        "When to use MLPE",
        "Load and inspect the data",
        "Build the conductance graph",
        "Fit candidate models",
        "Read the MLPE summary",
        "Coefficients are conditional on the other terms",
        "Check the fit and map conductance",
        "Does the extra term predict new sites?",
        "Quick reference",
        "Summary of key functions",
        "See also",
        "Reference"
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      "created": "2026-10-28 18:31:49",
      "modified": "2026-10-28 18:31:49",
      "commits": 1
    },
    {
      "source": "simulation-design.Rmd",
      "filename": "simulation-design.html",
      "title": "Simulating Covariance Data to Plan a Study",
      "author": "Bill Peterman",
      "engine": "knitr::rmarkdown",
      "headings": [
        "How many ponds would you sample?",
        "Keep the landscape and specify a new response",
        "Generate once and inspect recovery",
        "Compare site designs without changing the question",
        "Separate data information from assumed precision",
        "What can you take to the field?",
        "Summary of key functions",
        "See also"
      ],
      "created": "2026-05-29 23:55:38",
      "modified": "2026-10-28 18:31:49",
      "commits": 7
    },
    {
      "source": "spline-conductance.Rmd",
      "filename": "spline-conductance.html",
      "title": "Spline Conductance Models",
      "author": "Bill Peterman",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Shape and spatial context are different questions",
        "Use the same genotypes and fixed context",
        "See how basis functions build a curve",
        "Fit linear and spline candidates with starting checks",
        "Interpret the fitted association and its support",
        "View the genetic-response curve",
        "Ask whether flexibility earns its extra parameters",
        "What to take to your own study",
        "Quick reference: shape at a fixed context",
        "Summary of key functions",
        "See also"
      ],
      "created": "2026-05-12 03:49:11",
      "modified": "2026-10-28 18:31:49",
      "commits": 15
    }
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