`minSigCor`

is a helper function that estimates the minimum
significant correlation for a smaple size `n`

at a confidence level
defined by the argument `alpha`

.

1 |

`n` |
sample size or the length of a timeseries vector. |

`alpha` |
confidence level: the default is |

`r` |
a vector of values from |

`minSigCor`

function estimates the minimum significant correlation
for a sample size (number of observations or temporal points in a timeseries)
at a certain confidence level selected by the argument `alpha`

and an
optional search range `r`

. It is called by `validClimR`

function objective tree cut based on the specified confidence level.

A positive value beween `0`

and `1`

for the estimated the minimum
significant correlation.

Hamada Badr <badr@jhu.edu>, Ben Zaitchik <zaitchik@jhu.edu>, and Amin Dezfuli <dez@jhu.edu>.

Hamada S. Badr, Zaitchik, B. F. and Dezfuli, A. K. (2015):
A Tool for Hierarchical Climate Regionalization, *Earth Science Informatics*,
1-10, http://dx.doi.org/10.1007/s12145-015-0221-7.

Hamada S. Badr, Zaitchik, B. F. and Dezfuli, A. K. (2014):
Hierarchical Climate Regionalization, *CRAN*,
http://cran.r-project.org/package=HiClimR.

`HiClimR`

, `validClimR`

, `geogMask`

,
`coarseR`

, `fastCor`

, `grid2D`

, and
`minSigCor`

.

1 2 3 4 |

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