Forest Mensuration and Management
Generate the curve of a forest's average tree using the Kozak taper mo...
Classify a forest for selective cutting using the Meyer BDq method
Bias of an estimator in percentage
Check if character vector contains variable names
Classify a given variable and get center of class
Classify inventory data based on site index
Divide data into diameter classes, and get number of observations
Calculate the dominant height of forest inventory data plots
Estimate future and present basal area, volume, TCA, CMI and MMI value...
Fit the Clutter model for growth and yield
Get the forest horizontal, vertical and internal structure
Graybill F Test
Get the guide curve plot for growth and yield analysis of inventory da...
Calculate the volume with bark of trees using the Huber method
Calculate the volume without bark of trees using the Huber method
Identity of a Model Test
Calculate the inverse of a number
Fit linear regressions by group, with the option of removing outliers ...
Fit linear regressions, with the option of removing outliers using a i...
Fit linear regressions by group, and get different output options.
Convert NA to zero on numeric variables
Fit non-linear regressions by group, using LM algorithm and get differ...
Calculate Net Present Value and other economic variables
Calculate interquartile range
Pipe
Summarize forest inventory data
Raise a numeric vector to a given power
Calculate residual values and create plots
Remove empty columns
RMSE of an estimator in percentage
Round all numeric variables of a data frame to a given digit
Get the similarity matrix of an area
Calculate the volume with bark of trees using the Smalian method
Calculate the volume without bark of trees using the Smalian method
Get the aggregation state of species
Get the species diversity indexes
Simple Random Sampling
Systematic Sampling
Stratified Random Sampling
Tee
Calculate the equivalent diameter of trees with more than one trunk
Divide data into 3 vertical strata
Summarize volume of trees
Processing forest inventory data with methods such as simple random sampling, stratified random sampling and systematic sampling. There are also functions for yield and growth predictions and model fitting, linear and nonlinear grouped data fitting, and statistical tests. References: Kershaw Jr., Ducey, Beers and Husch (2016). <doi:10.1002/9781118902028>.
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