Description Details Author(s) References Examples

Fits spatial scale (SS) forward stepwise regression, SS incremental forward stagewise regression, SS least angle regression (LARS), and SS lasso models. All area-level covariates are considered at all available scales to enter a model, but the SS algorithms are constrained to select each area-level covariate at a single spatial scale.

Package: | spselect |

Type: | Package |

Version: | 0.0.1 |

Date: | 2016-08-29 |

License: | GPL (>=2) |

LazyLoad: | yes |

Lauren Grant, David Wheeler

Maintainer: Lauren Grant <pacele@vcu.edu>

Grant LP, Gennings C, Wheeler, DC. (2015). Selecting spatial scale of covariates in regression models of environmental exposures. Cancer Informatics, 14(S2), 81-96. doi: 10.4137/CIN.S17302

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```
Loading required package: tester
Loading required package: magic
Loading required package: abind
Loading required package: pracma
Attaching package: 'pracma'
The following object is masked from 'package:magic':
magic
[1] "Results are with no intercept."
[1] "Start: AIC = -1.0259"
[1] "y ~ 0"
[1] 1
[1] "Step: AIC = -10.3344"
[1] "y ~ ss1_x2.ss1"
[1] 2
[1] "Step: AIC = -13.6769"
y ~ ss1_x2.ss1 + ind_x1.ind
[1] "Diff in AIC = 3.3425"
[1] 3
[1] "Step: AIC = -22.6657"
y ~ ss1_x2.ss1 + ind_x1.ind + ss2_x3.ss2
[1] "Diff in AIC = 8.9887"
Call:
lm(formula = y ~ . - 1, data = X.in, x = TRUE, y = TRUE)
Coefficients:
ss1_x2.ss1 ind_x1.ind ss2_x3.ss2
0.6784 0.4703 0.4443
[1] "Diff in AIC = 8.9887"
[1] "Epsilon = 1"
[1] "No. of vars in model = 3"
[1] "Total no. of vars possible = 3"
```

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