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Rolling your own : linear model hypothesis testing and power calculations via the singular value decomposition
We outline the steps that would permit a statistician to produce special purpose linear model routines through the use of high quality public domain numerical analysis software.
https://www.fs.usda.gov/treesearch/search?keywords=%22Linear+models%22
Author(s):
Steve Verrill
Year:
2001
Keywords:
Linear models, hypothesis testing, singular value decomposition, power calculations
Source:
[Statistical computing & statistical graphics newsletter]. Vol. 12, no. 1 [2001]: Pages 15-18
The microcomputer scientific software series 2: general linear model--regression.
The general linear model regression (GLMR) program provides the microcomputer user with a sophisticated regression analysis capability. The output provides a regression ANOVA table, estimators of the regression model coefficients, their confidence intervals, confidence intervals around the predicted Y-values, residuals for plotting, a check for multicollinearity, a...
https://www.fs.usda.gov/treesearch/search?keywords=%22Linear+models%22
Author(s):
Harold M. Rauscher
Year:
1983
Keywords:
regression, microcomputer, BASIC, statistics
Source:
General Technical Report NC-85. St. Paul, MN: U.S. Dept. of Agriculture, Forest Service, North Central Forest Experiment Station
Using quadratic mean diameter and relative spacing index to enhance height-diameter and crown ratio models fitted to longitudinal data
The inclusion of quadratic mean diameter (QMD) and relative spacing index (RSI) substantially improved the predictive capacity of heightâdiameter at breast height (d.b.h.) and crown ratio models (CR), respectively. Data were obtained from 208 permanent plots established in western Arkansas and eastern Oklahoma during 1985â1987 and remeasured for the sixth time (2012â...
https://www.fs.usda.gov/treesearch/search?keywords=%22Linear+models%22
Author(s):
Pradip Saud; Thomas B. Lynch; Anup K. C.; James M. Guldin
Year:
2016
Keywords:
mixed-effects model, autocorrelation, height–d.b.h. relationship, crown ratio, quadratic mean diameter, relative spacing index
Source:
Forestry
Scale of association: hierarchical linear models and the measurement of ecological systems
A fundamental challenge to understanding patterns in ecological systems lies in employing methods that can analyse, test and draw inference from measured associations between variables across scales. Hierarchical linear models (HLM) use advanced estimation algorithms to measure regression relationships and variance-covariance parameters in hierarchically structured...
https://www.fs.usda.gov/treesearch/search?keywords=%22Linear+models%22
Author(s):
Sean M. McMahon; Jeffrey M. Diez
Year:
2007
Keywords:
bayesian statistics, hierarchical linear models, inference, maximum liklihood, multilevel models, regression, scale, variance components
Source:
Ecology letters, Vol. 10: 1-16
"Missing": A computer program for the maximum likelihood estimates of the parameters of the multivariate linear model with incomplete measurements.
https://www.fs.usda.gov/treesearch/search?keywords=%22Linear+models%22
Author(s):
Stanford Arner; Donald W. Seegrist
Year:
1980
Keywords:
Source:
Gen. Tech. Rep. NE-56. Broomall, PA: U. S. Department of Agriculture, Forest Service, Northeastern Forest Experimental Station. 19 p.
A computer program for the maximum likelihood estimator of the general multivariate linear model with correlated errors
https://www.fs.usda.gov/treesearch/search?keywords=%22Linear+models%22
Author(s):
Stanford L. Arner; Donald W. Seegrist
Year:
1979
Keywords:
Source:
Gen. Tech. Rep. NE-51. Broomall, PA: U. S. Department of Agriculture, Forest Service, Northeastern Forest Experimental Station. 10 p.
The microcomputer scientific software series 3: general linear model--analysis of variance.
A BASIC language set of programs, designed for use on microcomputers, is presented. This set of programs will perform the analysis of variance for any statistical model describing either balanced or unbalanced designs. The program computes and displays the degrees of freedom, Type I sum of squares, and the mean square for the overall model, the error, and each factor...
https://www.fs.usda.gov/treesearch/search?keywords=%22Linear+models%22
Author(s):
Harold M. Rauscher
Year:
1985
Keywords:
balanced designs, BASIC, unbalanced designs, TRS-80, singular value decomposition
Source:
General Technical Report NC-86. St. Paul, MN: U.S. Dept. of Agriculture, Forest Service, North Central Forest Experiment Station
A hierarchical linear model for tree height prediction.
Measuring tree height is a time-consuming process. Often, tree diameter is measured and height is estimated from a published regression model. Trees used to develop these models are clustered into stands, but this structure is ignored and independence is assumed. In this study, hierarchical linear models that account explicitly for the clustered structure of the data...
https://www.fs.usda.gov/treesearch/search?keywords=%22Linear+models%22
Author(s):
Vicente J. Monleon
Year:
2003
Keywords:
Source:
In: 2003 Joint Statistical Meetings - Section on Statistics & the Environment: 2865-2869
A Comparison of the Spatial Linear Model to Nearest Neighbor (k-NN) Methods for Forestry Applications
Forest surveys provide critical information for many diverse interests. Data are often collected from samples, and from these samples, maps of resources and estimates of aerial totals or averages are required. In this paper, two approaches for mapping and estimating totals; the spatial linear model (SLM) and k-NN (k-Nearest Neighbor) are compared, theoretically,...
https://www.fs.usda.gov/treesearch/search?keywords=%22Linear+models%22
Author(s):
Jay M. Ver Hoef; Hailemariam Temesgen; Sergio Gómez
Year:
2013
Keywords:
spatial modeling, nearest neighbor, imputation, spatial linear model
Source:
PLoS ONE. 8(3): e59129. 13 p.
Five instruments for measuring tree height: an evaluation
Five instruments were tested for reliability in measuring tree heights under realistic conditions. Four linear models were used to determine if tree height can be measured unbiasedly over all tree sizes and if any of the instruments were more efficient in estimating tree height. The laser height finder was the only instrument to produce unbiased estimates of the true...
https://www.fs.usda.gov/treesearch/search?keywords=%22Linear+models%22
Author(s):
Michael S. Williams; William A. Bechtold; V.J. LaBau
Year:
1994
Keywords:
Source:
south. J. Appl. For., Vol. 18(2): 76-82
Modeling nonlinear preferences
Economic theory, as well as intuition, supports the notion of increasing or decreasing marginal rates of substitution. That is, the marginal benefit derived from an increase in a desired good or service, or one's willingness to accept tradeoffs among various costs or' benefits, depends on the current mix or allocation. However, due to widespread availability...
https://www.fs.usda.gov/treesearch/search?keywords=%22Linear+models%22
Author(s):
Donald F. Dennis
Year:
2002
Keywords:
Source:
In: Todd, Sharon, comp., ed. 2002. Proceedings of the 2001 Northeastern Recreation Research Symposium. Gen. Tech. Rep. NE-289. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northeastern Research Station. 275-278.
Generalized linear models and point count data: statistical considerations for the design and analysis of monitoring studies
The success of avian monitoring programs to effectively guide management decisions requires that studies be efficiently designed and data be properly analyzed. A complicating factor is that point count surveys often generate data with non-normal distributional properties. In this paper we review methods of dealing with deviations from normal assumptions, and we focus...
https://www.fs.usda.gov/treesearch/search?keywords=%22Linear+models%22
Author(s):
Nathaniel E. Seavy; Suhel Quader; John D. Alexander; C. John Ralph
Year:
2005
Keywords:
Generalized linear models, juniper removal, monitoring, overdispersion, point count, Poisson
Source:
In: Ralph, C. John; Rich, Terrell D., editors 2005. Bird Conservation Implementation and Integration in the Americas: Proceedings of the Third International Partners in Flight Conference. 2002 March 20-24; Asilomar, California, Volume 2 Gen. Tech. Rep. PSW-GTR-191. Albany, CA: U.S. Dept. of Agriculture, Forest Service, Pacific Southwest Research Station: p. 744-753
Prediction of wood Quality in Small-Diameter Douglas-Fir using site and Stand Characteristics
Standing stress wave measurements were taken on 274 small-diameter Douglas-fir trees in western Montana. Stand, site, and soil measurements collected in the field and remotely through geographical information system (GIS) data layers were used to model dynamic modulus of elasticity (DMOE) in those trees. The best fit linear model developed resulted in an adjusted
https://www.fs.usda.gov/treesearch/search?keywords=%22Linear+models%22
Author(s):
C.D. Morrow; T.M. Gorman; J.W. Evans; D.E. Kretschmann; C.A. Hatfield
Year:
2013
Keywords:
Douglas-fir, nondestructive, MOE, prediction, soil, stand, least limiting water range (LLWR)
Source:
Wood and Fiber Science, Volume 45, Number 1, 2013; pp. 49-61.
The decline and fall of Type II error rates
For general linear models with normally distributed random errors, the probability of a Type II error decreases exponentially as a function of sample size. This potentially rapid decline reemphasizes the importance of performing power calculations.
https://www.fs.usda.gov/treesearch/search?keywords=%22Linear+models%22
Author(s):
S. P. Verrill; Mark Durst
Year:
2005
Keywords:
Asymptotic relative efficiency, experimental design, Hodges-Lehmann efficiency, linear models, Mills’ ratio, minimum detectable difference, noncentral F, normal tail, Pitman efficiency, power, sample size
Source:
American statistician. Vol. 59, no. 4 (Nov. 2005): pages 287-291.
The decline and fall of Type II error rates
For general linear models with normally distributed random errors, the probability of a Type II error decreases exponentially as a function of sample size. This potentially rapid decline reemphasizes the importance of performing power calculations.
https://www.fs.usda.gov/treesearch/search?keywords=%22Linear+models%22
Author(s):
Steve Verrill; Mark Durst
Year:
2005
Keywords:
Power, sample size, linear models, experimental design, noncentral F, normal tail, Mills’ ratio, asymptotic relative efficiency, Hodges-Lehmann efficiency, Pitman efficiency, minimum detectable difference
Source:
Research Paper FPL-RP-628. Madison, WI: U.S. Department of Agriculture, Forest Service, Forest Products Laboratory. 11 p.
A multivariate model and statistical method for validating tree grade lumber yield equations
Lumber yields within lumber grades can be described by a multivariate linear model. A method for validating lumber yield prediction equations when there are several tree grades is presented. The method is based on multivariate simultaneous test procedures.
https://www.fs.usda.gov/treesearch/search?keywords=%22Linear+models%22
Author(s):
Donald W. Seegrist
Year:
1975
Keywords:
Source:
Res. Pap. NE-320. Upper Darby, PA: U.S. Department of Agriculture, Forest Service, Northeastern Forest Experiment Station. 19p.
Comparing tree foliage biomass models fitted to a multispecies, felled-tree biomass dataset for the United States
tEstimation of live tree biomass is an important task for both forest carbon accounting and studies of nutri-ent dynamics in forest ecosystems. In this study, we took advantage of an extensive felled-tree database(with 2885 foliage biomass observations) to compare different models and grouping schemes based onphylogenetic and geographic variation for predicting foliage...
https://www.fs.usda.gov/treesearch/search?keywords=%22Linear+models%22
Author(s):
Brian J. Clough; Matthew B. Russell; Grant M. Domke; Christopher W. Woodall; Philip J. Radtke
Year:
2016
Keywords:
Foliage biomass models, Component ratio models, Bayesian hierarchical models, Posterior predictive checking, Prediction uncertainty
Source:
Ecological Modelling
Structural Change in Southern Softwood Stumpage Markets
The potential for structural change in southern stumpage market models has impacts on not only our basic understanding of those markets, but also on harvest, inventory and price projections, and related policy. In this paper, we test for structural change in both sawtimber and pulpwood softwood stumpage markets in the U.S. South over the period 1950-1994. Test...
https://www.fs.usda.gov/treesearch/search?keywords=%22Linear+models%22
Author(s):
Douglas R. Carter
Year:
1998
Keywords:
Source:
SOFEW 1998: Proceedings of the 1998 Southern Forest Economics Workshop
A diameter increment model for Red Fir in California and Southern Oregon
Periodic (10-year) diameter increment of individual red fir trees in Califomia and southern Oregon can be predicted from initial diameter and crown ratio of each tree, site index, percent slope, and aspect of the site. The model actually predicts the natural logarithm ofthe change in squared diameter inside bark between the startand the end of a 10-year growth period....
https://www.fs.usda.gov/treesearch/search?keywords=%22Linear+models%22
Author(s):
K. Leroy Dolph
Year:
1992
Keywords:
increment (diameter), California red fir, Shasta red fir, California, Oregon
Source:
Res. Paper PSW-RP-210. Albany, CA: Pacific Southwest Research Station, Forest Service, U.S. Department of Agriculture; 6 p
Post-Modeling Histogram Matching of Maps Produced Using Regression Trees
Spatial predictive models often use statistical techniques that in some way rely on averaging of values. Estimates from linear modeling are known to be susceptible to truncation of variance when the independent (predictor) variables are measured with error. A straightforward post-processing technique (histogram matching) for attempting to mitigate this effect is...
https://www.fs.usda.gov/treesearch/search?keywords=%22Linear+models%22
Author(s):
Andrew J. Lister; Tonya W. Lister
Year:
2006
Keywords:
Source:
In: Proceedings of the sixth annual forest inventory and analysis symposium; 2004 September 21-24; Denver, CO. Gen. Tech. Rep. WO-70. Washington, DC: U.S. Department of Agriculture Forest Service. 126p.
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