fithd: Fit a Height-Diameter model to forest tree data using...

In lmfor: Functions for Forest Biometrics

Fit a Height-Diameter model to forest tree data using functions of package nlme.

Description

Fits either linear or nonlinear Height-Diameter (H-D) model into a dataset of tree heights and diameters. Possible hierarchy of the data can be taken into account through random effects. Several commonly used nonlinear two-parameter H-D functions are available. Linear functions can be used as well.

Usage

fithd(d, h, plot=c(), modelName="naslund", nranp=2,
      random=NA, varf=0, na.omit=TRUE, start=NA, bh=1.3,
	  control = list(), SubModels=NA, vfstart=0)

Arguments

d	A numerical vector of tree diameters, usually given in cm.
h	A numerical vector of tree heights, usually given in meters. Should be of the same length as d.
plot	A vctor of type numeric or factor, defining the groups of the data; usually the plot indices. Should be of the same length as d and h.
modelName	Either (i) a character vector specifying the name of the nonlinear function or (ii) the formula specifying a linear model. In case (i) the name should be one of the functions documented on the help page of HDmodels. In case (ii), it should be the linear formula in the form that is entered to the function lme, for example model=h~d+I(d^2)-1
nranp, random	Parameters nranp and random specify two alternative ways to specify the random effects of the model. An easy but restricted way is to use argument nranp. It is an integer between 0 and the number of fixed parameters, and has the the following meaning in the case of nonlinear model: If nranp=0, then a model without random parameters is fitted. Results to a fixed-effects model, and argument plot is not used. If nranp=1, then parameter a of a nonlinear function or the first coefficient of the linear formula is assumed to vary among plots. If nranp=2, then a and b or the first two terms of the linear formula are assumed to vary among plots or If nranp=3, then a b, and c of a three-parameter nonlinear model or three first coefficients of a linear model are assumed to vary among plots In the case of linear model, the constant (if exists) it always counted as the first term. As an alternative to nranp, argument random can be used to express the random part as a nlme formula, but without specification of the grouping structure. The provided formula is passed to the lme or nlme function. Argument random is always used when provided, so nranp has effect only if random=NA (the default).
varf	Numeric with values 0, 1 or 2. If 0 or FALSE, no variance function is used. If varf=1, 2 or TRUE, then the power- type variance function var(e)=sigma^2*w^(2*delta) is used. where weight w is the raw diameter (when varf=1 or TRUE), or w=max(1,dsd+3) (when varf=2), where dsd=(d-D)/SDD. Here d is tree diameter, D and SDD are the mean and standard deviation of diameters on the plot in question.
na.omit	Should missing heights be omitted. Defaults to TRUE.
start	A vector of the starting values of the parameters of the nlme fit. If NA, then the starting values are computed using the function computing the starting values (e.g., startHDnaslund, see HDmodels).
bh	The applied breast height. Defaults to 1.3 (meters).
control	Parameters to control of the model fitting algorithm, see nlmeControl for details.
SubModels	Implemented only for nonlinear models. A character vector of length 2 or 3, according to the number of parameters in the model. It allows submodels for parameters a, b (and c), where the parameter is explaiend by plot-specific mean diameter ("~dmean"), plot-specific standard deviation "~dsd", or diameter standardized at plot level ("~dstd"), when the predictor is (d-D)/SDD (see teh documentation of argument varf). Defaults to NA, which corresponds to no submodels, or submodels=c("~1","~1","1")
vfstart	Starting value of the power parameter delta of the variance function. Defaults to 0.

Details

Depending on the model (nonlinear or linear, mixed-effects model or marginal), the the model is fitted using one of the following functions functions of the nlme package: nlme, lme, gls or gnls.

See available H-D functions at HDmodels. The user can define her own new functions as specified at HDmodels.

Value

An object of class hdmod, inheriting from class nlme.

Author(s)

Lauri Mehtatalo <[e-mail]>

References

Mehtatalo, L., Gregoire, T.G., and de Miguel, S. Modeling Height-diameter curves for height prediction. Canadian Journal of Forest Research, 45(7): 826-837, doi: 10.1139/cjfr-2015-0054

See Also

HDmodels for the available functions, Functions nlme, lme, gls or gnls for details on model fitting, ImputeHeights for imputing unobserved tree heights.

Examples

data(spati)

fithd(spati$d,spati$h,spati$plot)
fithd(spati$d,spati$h,spati$plot,SubModels=c("dmean","log(dmean)"),varf=2)

lmfor documentation built on April 30, 2022, 1:08 a.m.