alts2dups
(Package: rgr) :
Create a Matrix of Duplicate Pairs from Sequential Data
Function to take data stored as stacked records or alternating rows of records for ndup duplicate pairs and generate a matrix with ndup rows and two columns for the duplicate data, for further details see x in Arguments below. The function returns a matrix for processing.
● Data Source:
CranContrib
● Keywords: manip, misc
● Alias: alts2dups
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gx.ngr.summary
(Package: rgr) :
Saves a NGR Report Summary Statistics Table to a .csv File
Prepares a .csv file with the standard set of NGR Report summary statistics for further processing with a spread sheet program. The table includes: N (data set size), number of NAs, mean, SD, skew, CV%, geometric mean, median, MAD, robust CV%, and the miniumum and maximum values and 17 intermediate percentiles.
● Data Source:
CranContrib
● Keywords: univar
● Alias: gx.ngr.summary
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var2fact
(Package: rgr) :
Rearranges Data for Variables as Factors
Rearranges data from a matrix or data frame into a matrix where data are tagged by their variables names as factors. Used to concatenate data for display with functions tbplots.by.var and bwplots.by.var.
● Data Source:
CranContrib
● Keywords: misc
● Alias: var2fact
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xyplot.eda8
(Package: rgr) :
Display a Third Variable in a X-Y Plot as Percentiles
Displays a third variable on a X-Y plot where the the third variable is represented by symbols indicating within which group defined by the data's 2nd, 5th, 25th, 50th, 75th, 95th and 98th percentiles plotted a data value falls. The colours of the symbols may be optionally changed. The x-y plot axes may be optionally displayed with logarithmic (base 10) scaling. Optionally a legend (two options) may be added to the plot.
● Data Source:
CranContrib
● Keywords: hplot
● Alias: xyplot.eda8
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gx.ngr.skew
(Package: rgr) :
Estimate the Skewness of a Data Vector
Estimates the skew of a data vector for gx.ngr.stats to be used by gx.ngr.summary to output a NGR Table of summary statistics as a ‘.csv’ file.
● Data Source:
CranContrib
● Keywords: univar
● Alias: gx.ngr.skew
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gx.hypergeom
(Package: rgr) :
Compute Probabilities for Target Recognition
The hypergeometric distribution is used to infer if the number of anomalous sites along a traverse reliably reflect the presence of the dispersion pattern from a known mineral occurrence. The function displays the probability of the observed outcome could be due to chance alone.
● Data Source:
CranContrib
● Keywords: htest
● Alias: gx.hypergeom
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xyplot.z
(Package: rgr) :
Display a Third Variable in a X-Y Plot using Proportional Symbols
Displays a third variable where the data are represented by open circles whose diameters are proportional to the value of the data at their x-y locations. The rate of change of symbol diameter with value and the absolute size of the symbols are defined by the user. The x-y plot axes may be optionally displayed with logarithmic (base 10) scaling. Optionally a legend may be displayed on the plot.
● Data Source:
CranContrib
● Keywords: hplot
● Alias: xyplot.z
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gx.ngr.stats
(Package: rgr) :
Computes Summary Statistics for a NGR Report Table
Builds a vector of summary statistics for gx.ngr.summary to output a NGR Report table of summary statistics as a ‘.csv’ file from estimates made by gx.stats and gx.ngr.skew.
● Data Source:
CranContrib
● Keywords: univar
● Alias: gx.ngr.stats
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display.lty
(Package: rgr) :
Display Available Line Styles and Colour Codes
Displays the line styles and colours corresponding to lty = 1 to 9 and colr = 1 to 9, respectively.
● Data Source:
CranContrib
● Keywords: color, misc
● Alias: display.lty
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caplot
(Package: rgr) :
Prepare a Concentration-Area (C-A) Plot
Displays a concentration-area (C-A) plot to assess whether the data are spatially multi-fractal (Cheng et al., 1994; Cheng and Agterberg, 1995) as a part of a four panel display. This procedure is useful for determining if multiple populations that are spatially dependent are present in a data set. It can be used to determine the practical limits, upper or lower bounds, of the influence of the biogeochemical processes behind the spatial distribution of the data. Optionally the data may be logarithmically transformed (base 10) prior to interpolation, the points may be ‘jittered’ (see Arguments below), the size of the interpolated grid may be modified, and alternate colour schemes can be chosen for display of the interpolated data.
● Data Source:
CranContrib
● Keywords: hplot
● Alias: caplot
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providing 
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