Simulated data and code for analysis of herpetofauna response to forest management in the Missouri Ozarks

Christopher T. Rota; Alexander J. Wolf; Rochelle B. Renken; Robert A. Gitzen; Debby K. Fantz; Robert A. Montgomery; Matthew G. Olson; Larry D. Vangilder; Joshua J. Millspaugh

doi:10.1016/j.dib.2016.08.043

Simulated data and code for analysis of herpetofauna response to forest management in the Missouri Ozarks

Christopher T. Rota, Alexander J. Wolf, Rochelle B. Renken, Robert A. Gitzen, Debby K. Fantz, Robert A. Montgomery, Matthew G. Olson, Larry D. Vangilder, Joshua J. Millspaugh

Research output: Contribution to journal › Article › peer-review

Abstract

We present predictor variables and R and Stan code for simulating and analyzing counts of Missouri Ozark herpetofauna in response to three forest management strategies. Our code performs four primary purposes: import predictor variables from spreadsheets; simulate synthetic response variables based on imported predictor variables and user-supplied values for data-generating parameters; format synthetic data for export to Stan; and analyze synthetic data.

Original language	English
Pages (from-to)	477-479
Number of pages	3
Journal	Data in Brief
Volume	9
DOIs	https://doi.org/10.1016/j.dib.2016.08.043
State	Published - Dec 2016

Funding

The Missouri Ozark Forest Ecosystem Project (MOFEP) is funded by the Missouri Department of Conservation (cooperative agreement #305) , and conducted by the Missouri Department of Conservation, the University of Missouri, the U.S. Forest Service, and other collaborators. We thank the many technicians who have assisted with MOFEP, particularly those contributing to the herpetofauna study.

Funders	Funder number
Missouri Department of Conservation	305
U.S. Forest Service-Retired
Southeast Missouri State University

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title = "Simulated data and code for analysis of herpetofauna response to forest management in the Missouri Ozarks",

abstract = "We present predictor variables and R and Stan code for simulating and analyzing counts of Missouri Ozark herpetofauna in response to three forest management strategies. Our code performs four primary purposes: import predictor variables from spreadsheets; simulate synthetic response variables based on imported predictor variables and user-supplied values for data-generating parameters; format synthetic data for export to Stan; and analyze synthetic data.",

author = "Rota, {Christopher T.} and Wolf, {Alexander J.} and Renken, {Rochelle B.} and Gitzen, {Robert A.} and Fantz, {Debby K.} and Montgomery, {Robert A.} and Olson, {Matthew G.} and Vangilder, {Larry D.} and Millspaugh, {Joshua J.}",

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AU - Rota, Christopher T.

AU - Wolf, Alexander J.

AU - Renken, Rochelle B.

AU - Gitzen, Robert A.

AU - Fantz, Debby K.

AU - Montgomery, Robert A.

AU - Olson, Matthew G.

AU - Vangilder, Larry D.

AU - Millspaugh, Joshua J.

PY - 2016/12

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AB - We present predictor variables and R and Stan code for simulating and analyzing counts of Missouri Ozark herpetofauna in response to three forest management strategies. Our code performs four primary purposes: import predictor variables from spreadsheets; simulate synthetic response variables based on imported predictor variables and user-supplied values for data-generating parameters; format synthetic data for export to Stan; and analyze synthetic data.

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SP - 477

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ER -

Simulated data and code for analysis of herpetofauna response to forest management in the Missouri Ozarks

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