Description Usage Arguments Details Value Author(s) References Examples
Bootstrapbased procedure that tests whether the data can be modelled by an allometric model.
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formula 
An object of class 
data 
An optional data frame, matrix or list required by
the formula. If not found in data, the variables are taken from

na.action 
A function which indicates what should happen when the data contain 'NA's. The default is 'na.omit'. 
nboot 
Number of bootstrap repeats. 
seed 
Seed to be used in the bootstrap procedure. 
cluster 
A logical value. If 
ncores 
An integer value specifying the number of cores to be used
in the parallelized procedure. If 
test 
Statistic test to be used, based on residuals on the null model
( 
... 
Other options. 
In order to facilitate the choice of a model appropriate
to the data while at the same time endeavouring to minimise the
loss of information, a bootstrapbased procedure, that test whether the
data can be modelled by an allometric model, was developed. Therefore,
allotest
tests the null hypothesis of an allometric model taking
into account the logarithm of the original variable
(X^* = log(X) and Y^* = log(Y)).
Based on a general model of the type
Y^*=m(X^*)+\varepsilon
the aim here is to test the null hypothesis of an allometric model
H_0 = m(x^*) = a^*+ b^* x^*
vs. the general hypothesis H_1, with m being an unknown nonparametric function; or analogously,
H_1: m(x^*)= a^*+ b^* x^* + g(x^*)
with g(x^*) being an unknown function not equal to zero.
To implement this test we have used the wild bootstrap.
An object is returned with the following elements:
statistic 
the value of the test statistic. 
value 
the pvalue of the test. 
Marta Sestelo, Nora M. Villanueva and Javier RocaPardinas.
Sestelo, M. and RocaPardinas, J. (2011). A new approach to estimation of lengthweight relationship of Pollicipes pollicipes (Gmelin, 1789) on the Atlantic coast of Galicia (Northwest Spain): some aspects of its biology and management. Journal of Shellfish Research, 30 (3), 939–948.
Sestelo, M. (2013). Development and computational implementation of estimation and inference methods in flexible regression models. Applications in Biology, Engineering and Environment. PhD Thesis, Department of Statistics and O.R. University of Vigo.
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