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2 | 2 | title: "DHARMa: residual diagnostics for hierarchical (multi-level/mixed) regression models"
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3 | 3 | author: "Florian Hartig, Theoretical Ecology, University of Regensburg [website](https://www.uni-regensburg.de/biologie-vorklinische-medizin/theoretische-oekologie/mitarbeiter/hartig/)"
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4 | 4 | date: "`r Sys.Date()`"
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5 |
| -output: |
6 |
| - pdf_document: |
7 |
| - toc: true |
| 5 | +output: |
8 | 6 | rmarkdown::html_vignette:
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9 | 7 | toc: true
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10 |
| -vignette: > |
11 |
| - %\VignetteIndexEntry{Vignette for the DHARMa package} |
12 |
| - \usepackage[utf8]{inputenc} |
13 |
| - %\VignetteEngine{knitr::rmarkdown} |
14 |
| -abstract: "The 'DHARMa' package uses a simulation-based approach to create readily interpretable scaled (quantile) residuals for fitted generalized linear (mixed) models. Currently supported are linear and generalized linear (mixed) models from 'lme4' (classes 'lmerMod', 'glmerMod'), 'glmmTMB', 'GLMMadaptive' and 'spaMM', generalized additive models ('gam' from 'mgcv'), 'glm' (including 'negbin' from 'MASS', but excluding quasi-distributions) and 'lm' model classes. Moreover, externally created simulations, e.g. posterior predictive simulations from Bayesian software such as 'JAGS', 'STAN', or 'BUGS' can be processed as well. The resulting residuals are standardized to values between 0 and 1 and can be interpreted as intuitively as residuals from a linear regression. The package also provides a number of plot and test functions for typical model misspecification problems, such as over/underdispersion, zero-inflation, and residual spatial and temporal autocorrelation. \n \n \n" |
15 |
| -editor_options: |
| 8 | + pdf_document: |
| 9 | + toc: true |
| 10 | +vignette: | |
| 11 | + %\VignetteIndexEntry{Vignette for the DHARMa package} \usepackage[utf8]{inputenc} %\VignetteEngine{knitr::rmarkdown} |
| 12 | +abstract: "The 'DHARMa' package uses a simulation-based approach to create readily |
| 13 | + interpretable scaled (quantile) residuals for fitted generalized linear (mixed) |
| 14 | + models. Currently supported are linear and generalized linear (mixed) models from |
| 15 | + 'lme4' (classes 'lmerMod', 'glmerMod'), 'glmmTMB', 'GLMMadaptive' and 'spaMM'; phylogenetic |
| 16 | + linear models from 'phylolm' (classes 'phylolm' and 'phyloglm'); generalized additive |
| 17 | + models ('gam' from 'mgcv'); 'glm' (including 'negbin' from 'MASS', but excluding |
| 18 | + quasi-distributions) and 'lm' model classes. Moreover, externally created simulations, |
| 19 | + e.g. posterior predictive simulations from Bayesian software such as 'JAGS', 'STAN', |
| 20 | + or 'BUGS' can be processed as well. The resulting residuals are standardized to |
| 21 | + values between 0 and 1 and can be interpreted as intuitively as residuals from a |
| 22 | + linear regression. The package also provides a number of plot and test functions |
| 23 | + for typical model misspecification problems, such as over/underdispersion, zero-inflation, |
| 24 | + and residual spatial, temporal and phylogenetic autocorrelation. \n \n \n" |
| 25 | +editor_options: |
16 | 26 | chunk_output_type: console
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17 | 27 | ---
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18 | 28 |
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