Description Usage Arguments Details Value Note Author(s) References Examples
Plots Vianelly (generalized Gaussian) density with finite range in [-1,1].
1 |
L1 |
positive shape parameter. |
L2 |
positive shape parameter. Impacts more on the tails. |
add |
when add=TRUE the plot is superimposed to an existing graph. |
lwd |
weight of the line. |
lty |
the type of the line. |
col |
color of the curve. |
ylim |
numeric vectors of length 2, giving the y coordinates ranges. |
Main |
a string describing the graph. |
np |
number of points to be plotted. |
The VGGFR density is given by
f(r;λ_1,λ_2)=λ_1(1-|r|^{λ_2})^{λ_1}/[2B(1/λ_1,λ_2+1)]
where λ_1,λ_2>0 and B() is the beta function.
The value returned is a list contaning:
st.dev |
standard deviation |
kurt |
kurtosis |
oam |
ordinate at the mode |
If you want to use the output from VGGFR save the result and then select from the list the value(s) needed.
Agostino Tarsitano and Ilaria Lucrezia Amerise
Tarsitano, A. and Amerise, I. L. (2016). "Modelling of the null distribution of rank correlations". Submitted.
Vianelli, S. (1968). "Sulle curve normali di ordine $r$ per intervalli finiti delle variabili statistiche". Annali della Facolt\‘a di Economia e Commercio dell’Universit\'a di Palermo, 2.
Vianelli, S. (1983). "The family of normal and lognormal distributions of order r". Metron, 41, 3-10.
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# Density curve of a VGGFR model
VGGFR(2, 12, add=FALSE, lwd=2, lty=5, col="darkgreen", ylim=c(0,2), Main="", np=201)
#####
#
a<-ranktes(0.5, 28, "r4", "vg",FALSE, "two", FALSE)
b<-VGGFR(a$Lambda, add = FALSE, lwd = 2, lty = 5, col = "blue", ylim=c(0,2.5),np = 201)
#####
#
# Lambert's semicircular distribution of errors (1760,1765).
# Given a probability distribution, the value with the higher probability density is
# deemed to be more probable than the value with the lower probability density.
#
VGGFR(2,0.5,col="red",ylim=c(0,0.75),Main="Lambert's distribution of errors")
#
#####
# Pearson type II used as an approximation to the null distribution of the Fisher-Yates
# rank correlation. Fieller, E. C. and Pearson, E. S. (1961). Tests for rank correlation
# coefficients: II. Biometrika, 48, 29-40.
n<-10
VGGFR(2, (n-4)/2, add=FALSE, lwd=2, lty=5, col="magenta2", ylim=c(0,1.1), Main="", np=201)
abline(h=0);abline(v=0,lty=2,lwd=2,col="pink2")
#####
#
# Save and use the results
res<-VGGFR(1.5,5.5,add = FALSE, lwd = 2, lty = 1, col = "blue", ylim=c(0,2.5),np = 201)
res$kurt-res$oam/res$st.dev
#####
#
# A family of symmetrical beta densities
VGGFR(2,1,col="black",ylim=c(0,1.4),Main="Symmetrical beta densities")
La<-seq(1,6,0.5)
for (L1 in La){VGGFR(2,L1,add=TRUE, lwd = 1, lty = 1, col=gray(L1/6))}
#####
#
# A family of GGFR curves
VGGFR(1,2, lwd = 1, lty = 1,col="black",ylim=c(0,5))
La<-seq(1,6,0.5);Lg<-seq(0,1,1/12)
for (L1 in La){
c2<-gray(Lg, alpha= 2/6)
for (L2 in seq(1,12,1)){
VGGFR(L1,L2,add=TRUE, lwd = 1, lty = 1, col=c2[L2])
}}
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