### Abstract

A model to predict the probability of merchantability for an individual loblolly pine tree is developed. The model would be a useful addition to diameter distribution-based yield models. As the dependent variable is discrete and bounded by 0,1, the model is constrained to yield predictions in this interval. Graphical techniques were used to screen potential independent variables, and maximum likelihood was used to estimate the model parameters.- Authors

Original language | English (US) |
---|---|

Pages (from-to) | 254-261 |

Number of pages | 8 |

Journal | Forest Science |

Volume | 32 |

Issue number | 1 |

State | Published - Jan 1 1986 |

Externally published | Yes |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Forestry
- Ecology
- Ecological Modeling

### Cite this

*Forest Science*,

*32*(1), 254-261.

}

*Forest Science*, vol. 32, no. 1, pp. 254-261.

**Merchantability of loblolly pine - an application of nonlinear regression with a discrete dependent variable.** / Strub, M. R.; Green, Edwin; Burkhart, H. E.; Pirie, W. R.

Research output: Contribution to journal › Article

TY - JOUR

T1 - Merchantability of loblolly pine - an application of nonlinear regression with a discrete dependent variable.

AU - Strub, M. R.

AU - Green, Edwin

AU - Burkhart, H. E.

AU - Pirie, W. R.

PY - 1986/1/1

Y1 - 1986/1/1

N2 - A model to predict the probability of merchantability for an individual loblolly pine tree is developed. The model would be a useful addition to diameter distribution-based yield models. As the dependent variable is discrete and bounded by 0,1, the model is constrained to yield predictions in this interval. Graphical techniques were used to screen potential independent variables, and maximum likelihood was used to estimate the model parameters.- Authors

AB - A model to predict the probability of merchantability for an individual loblolly pine tree is developed. The model would be a useful addition to diameter distribution-based yield models. As the dependent variable is discrete and bounded by 0,1, the model is constrained to yield predictions in this interval. Graphical techniques were used to screen potential independent variables, and maximum likelihood was used to estimate the model parameters.- Authors

UR - http://www.scopus.com/inward/record.url?scp=0022919989&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0022919989&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:0022919989

VL - 32

SP - 254

EP - 261

JO - Forest Science

JF - Forest Science

SN - 0015-749X

IS - 1

ER -