This function provides an empirical covariance function for data
CMBDataFrame or data.frame. It assumes that data are from a stationary spherical
random field and the covariance depends only on a geodesic distance between locations.
Output is a binned covariance.
specifies the number of bins
optionally specify the size of a simple random sample to take before calculating covariance. This may be useful if the full covariance computation is too slow.
an optional number between 0 and pi specifying the
maximum geodesic distance to use for calculating covariance. Only
optionally specify the breaks manually using a
vector giving the break points between cells. This vector
if TRUE then the bins have equal spherical area. If false then the bins have equal annular widths. Default is TRUE.
if TRUE then the
An object of the class CMBCovariance that is a modification of
from the package geoR with variogram values replaced by covariances.
The attribute "breaks" contains the break points used to create bins.
The result has
num.bins + 1 values since the first value, the sample
variance, is not counted as a bin.
a vector with distances.
a vector with estimated covariance values at distances given in u.
number of pairs in each bin
standard deviation of the values in each bin
limits defining the interval spanned by each bin
a logical vector indicating whether the number of pairs in each bin is greater or equal to the value in the argument pairs.min
variance of the data
parameters of the mean part of the model fitted by ordinary least squares
echoes the option argument
maximum distance between pairs allowed in the covariance calculations
number of data
direction for which the covariance was computed
the function call
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## Download the map first # downloadCMBMap(foreground = "smica", nside = 1024) # df <- CMBDataFrame("CMB_map_smica1024.fits") # cmbdf <- sampleCMB(df, sample.size = 100000) # Cov <- covCMB(cmbdf, max.dist = 0.03, num.bins = 10) # Cov
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