Last data update: 2014.03.03

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Results 1 - 10 of 44 found.
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zipfR.plotutils (Package: zipfR) : Plotting Utilities (zipfR)

Conveniently create plots with different layout and in different output formats (both on-screen and various graphics file formats).
● Data Source: CranContrib
● Keywords: device
● Alias: zipfR.begin.plot, zipfR.end.plot, zipfR.pick.device, zipfR.plotutils
● 0 images

zipfR.par (Package: zipfR) : Set or Query Graphics Parameters (zipfR)

Set default graphics parameters for zipfR high-level plots and plot utilities, similar to par for general graphics parameters. The current parameter values are queried by giving their names as character strings. The values can be set by specifying them as arguments in name=value form, or by passing a single list of named values.
● Data Source: CranContrib
● Keywords: iplot
● Alias: zipfR.par
● 0 images

zipfR-package (Package: zipfR) :

The zipfR package performs Large-Number-of-Rare-Events (LNRE) modeling of (linguistic) type frequency distributions (Baayen 2001) and provides utilities to run various forms of lexical statistics analysis in R.
● Data Source: CranContrib
● Keywords: package
● Alias: zipfR, zipfR-package
● 0 images

VV-Vm (Package: zipfR) : Variances of the Expected Frequency Spectrum (zipfR)

VV and VVm are generic methods that can (and should) be used to compute the variance of the vocabulary size and the variances of spectrum elements according to an LNRE model (i.e. an object of class lnre). These methods are also used to access variance information stored in some objects of class spc and vgc.
● Data Source: CranContrib
● Keywords: distribution, manip, methods, models
● Alias: VV, VVm
● 0 images

vgc.interp (Package: zipfR) : Expected Vocabulary Growth by Binomial Interpolation (zipfR)

vgc.interp computes the expected vocabulary growth curve for random sample taken from a data set described by the frequency spectrum object obj.
● Data Source: CranContrib
● Keywords: distribution, manip
● Alias: vgc.interp
● 0 images

vgc (Package: zipfR) : Vocabulary Growth Curves (zipfR)

In the zipfR library, vgc objects are used to represent a vocabulary growth curve (VGC). This can be an observed VGC from an incremental set of sample (such as a corpus), a randomized VGC obtained by binomial interpolation, or the expected VGC according to a LNRE model.
● Data Source: CranContrib
● Keywords: classes
● Alias: vgc, vgc.object
● 0 images

vec2xxx (Package: zipfR) : Type-Token Statistics for Samples and Empirical Data (zipfR)

Compute type-frequency list, frequency spectrum and vocabulary growth curve from a token vector representing a random sample or an observed sequence of tokens.
● Data Source: CranContrib
● Keywords: manip
● Alias: vec2spc, vec2tfl, vec2vgc
● 0 images

tfl (Package: zipfR) : Type Frequency Lists (zipfR)

In the zipfR library, tfl objects are used to represent a type frequency list, which specifies the observed frequency of each type in a corpus. For mathematical reasons, expected type frequencies are rarely considered.
● Data Source: CranContrib
● Keywords: classes
● Alias: tfl, tfl.object
● 0 images

spc.vector (Package: zipfR) : Create Vector of Spectrum Elements (zipfR)

spc.vector returns a selected range of elements from a frequency spectrum as a plain numeric vector (which may contain entries with V_m = 0, unlike the spc object itself).
● Data Source: CranContrib
● Keywords: manip
● Alias: spc.vector
● 0 images

spc.interp (Package: zipfR) : Expected Frequency Spectrum by Binomial Interpolation (zipfR)

spc.interp computes the expected frequency spectrum for a random sample of specified size N, taken from a data set described by the frequency spectrum object obj.
● Data Source: CranContrib
● Keywords: distribution, manip
● Alias: spc.interp
● 0 images