Description Usage Arguments Value References Examples

This function provides an empirical variogram for data in a
`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 variogram.

1 2 | ```
variogramCMB(cmbdf, num.bins = 10, sample.size, max.dist = pi, breaks,
equiareal = TRUE, calc.max.dist = FALSE)
``` |

`cmbdf` |
is a |

`num.bins` |
specifies the number of bins |

`sample.size` |
optionally specify the size of a simple random sample to take before calculating variogram. This may be useful if the full covariance computation is too slow. |

`max.dist` |
an optional number between 0 and pi specifying the
maximum geodesic distance to use for calculating covariance. Only
used if |

`breaks` |
optionally specify the breaks manually using a
vector giving the break points between cells. This vector
has length |

`equiareal` |
if TRUE then the bins have equal spherical area. If false then the bins have equal annular widths. Default is TRUE. |

`calc.max.dist` |
if TRUE then the |

An object of class `variog`

specified in the package **geoR**.

The attribute "breaks" contains the break points used to create bins.
The result has `num.bins + 1`

values since the first value at distance 0 is not
counted as a bin.

- u
a vector with distances.

- v
a vector with estimated variogram values at distances given in u.

- n
number of pairs in each bin

- sd
standard deviation of the values in each bin

- bins.lim
limits defining the interval spanned by each bin

- ind.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

- var.mark
variance of the data

- beta.ols
parameters of the mean part of the model fitted by ordinary least squares

- output.type
echoes the option argument

- max.dist
maximum distance between pairs allowed in the variogram calculations

- n.data
number of data

- direction
direction for which the variogram was computed

- call
the function call

**geoR** package, `variog`

, `covCMB`

, `corrCMB`

1 2 3 4 5 6 | ```
## Download the map first
# downloadCMBMap(foreground = "smica", nside = 1024)
# df <- CMBDataFrame("CMB_map_smica1024.fits")
# cmbdf <- sampleCMB(df, sample.size = 100000)
# varcmb <- variogramCMB(cmbdf, max.dist = 0.1, num.bins = 30, sample.size=100)
# varcmb
``` |

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