logbtcf {FSA} R Documentation

## Constructs the correction-factor used when back-transforming log-transformed values.

### Description

Constructs the correction-factor used when back-transforming log-transformed values according to the method in Sprugel (1983). Sprugel's main formula – exp((syx^2)/2) – is used when syx is estimated for natural log transformed data. He noted that a formula for any based could be constructed by multiplying the syx term by log_e(base) to give exp(((log_e(base)*syx)^2)/2). This more general formula is implemented in this function (where, of course, if the base is exp(1) then the general formula reduces to the original specific formula.)

### Usage

logbtcf(obj, base = exp(1))

### Arguments

 obj An object from lm. base A single numeric that indicates the base of the logarithm used.

### Value

A numeric value that is the correction factor according to Sprugel (1983).

### Author(s)

Derek H. Ogle, derek@derekogle.com

### References

Sprugel, D.G. 1983. Correcting for bias in log-transformed allometric equations. Ecology 64:209-210.

### Examples

# toy data
df <- data.frame(y=rlnorm(10),x=rlnorm(10))
df\$logey <- log(df\$y)
df\$log10y <- log10(df\$y)
df\$logex <- log(df\$x)
df\$log10x <- log10(df\$x)

# model and predictions on loge scale
lme <- lm(logey~logex,data=df)
( ploge <- predict(lme,data.frame(logex=log(10))) )
( pe <- exp(ploge) )
( cfe <- logbtcf(lme) )
( cpe <- cfe*pe )

# model and predictions on log10 scale
lm10 <- lm(log10y~log10x,data=df)
plog10 <- predict(lm10,data.frame(log10x=log10(10)))
p10 <- 10^(plog10)
( cf10 <- logbtcf(lm10,10) )
( cp10 <- cf10*p10 )

# cfe and cf10, cpe and cp10 should be equal
all.equal(cfe,cf10)
all.equal(cpe,cp10)

[Package FSA version 0.8.18 Index]