block.raw_cf: Block average correlation function data
In hadron: Analysis Framework for Monte Carlo Simulation Data in Physics
block.raw_cf R Documentation
Block average correlation function data
Description
Block block_length sequential measurements of the correlation
function together. This occurs, for example, when multiple
stochastic noise vectors are used per measurement or multiple
source locations. Alternatively, it can also be used to
account for auto-correlations in the data. If the total number
of measurements is not divisible by block_length, the last
measurements are discarded.
Usage
block.raw_cf(cf, block_length)
Arguments
cf
raw_cf object
block_length
Integer, number of successive measurements to average over.
Value
cf raw_cf object with the data member reduced in its first dimension
by a factor of block_length and restricted (at the end) to the number
of measurements divisible by block_length.
hadron documentation built on Sept. 9, 2022, 5:06 p.m.
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| block.raw_cf | R Documentation |
Block average correlation function data
Description
Block block_length sequential measurements of the correlation
function together. This occurs, for example, when multiple
stochastic noise vectors are used per measurement or multiple
source locations. Alternatively, it can also be used to
account for auto-correlations in the data. If the total number
of measurements is not divisible by block_length, the last
measurements are discarded.
Usage
block.raw_cf(cf, block_length)
Arguments
cf |
|
block_length |
Integer, number of successive measurements to average over. |
Value
cf raw_cf object with the data member reduced in its first dimension
by a factor of block_length and restricted (at the end) to the number
of measurements divisible by block_length.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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