Pool Data from Several Ratio Objects
Pool the data from several ratio objects
(objects of class "rat")
and compute a pooled estimate.
## S3 method for class 'rat' pool(..., weights=NULL, relabel=TRUE, variance=TRUE)
... |
Objects of class |
weights |
Numeric vector of weights. |
relabel |
Logical value indicating whether the result should be relabelled to show that it was obtained by pooling. |
variance |
Logical value indicating whether to compute the sample variance and related terms. |
The function pool is generic. This is the method for the
class "rat" of ratio objects. It is used to
combine several estimates of the same quantity
when each estimate is a ratio.
Each of the arguments ... must be an object of class
"rat" representing a ratio object (basically a
numerator and a denominator; see rat).
We assume that these ratios are all estimates of the same quantity.
If the objects are called R[1], …, R[n] and if R[i] has numerator Y[i] and denominator X[i], so that notionally R[i] = Y[i]/X[i], then the pooled estimate is the ratio-of-sums estimator
R = (Y[1]+…+Y[n])/(X[1]+…+X[n]).
The standard error of R is computed using the delta method as described in Baddeley et al. (1993) or Cochran (1977, pp 154, 161).
If the argument weights is given, it should be a numeric vector
of length equal to the number of objects to be pooled.
The pooled estimator is the ratio-of-sums estimator
R = (w[1] * Y[1]+…+ w[n] * Y[n])/(w[1] * X[1]+…+w[n] * X[n])
where w_iw[i] is the ith weight.
This calculation is implemented only for certain classes of objects where the arithmetic can be performed.
This calculation is currently implemented only for objects which
also belong to the class "fv" (function value tables).
For example, if Kest is called with argument
ratio=TRUE, the result is a suitable object (belonging to the classes
"rat" and "fv").
Warnings or errors will be issued if the ratio objects ...
appear to be incompatible. However, the code is not smart enough to
decide whether it is sensible to pool the data.
An object of the same class as the input.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner r.turner@auckland.ac.nz and Ege Rubak rubak@math.aau.dk.
Baddeley, A.J, Moyeed, R.A., Howard, C.V. and Boyde, A. (1993) Analysis of a three-dimensional point pattern with replication. Applied Statistics 42, 641–668.
Cochran, W.G. (1977) Sampling techniques, 3rd edition. New York: John Wiley and Sons.
K1 <- Kest(runifpoint(42), ratio=TRUE, correction="iso")
K2 <- Kest(runifpoint(42), ratio=TRUE, correction="iso")
K3 <- Kest(runifpoint(42), ratio=TRUE, correction="iso")
K <- pool(K1, K2, K3)
plot(K, pooliso ~ r, shade=c("hiiso", "loiso"))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.