R language Learning Note-probability function

In the R language, different distributions can be generated for experimentation and learning.

In R, the probability function is shaped like ①:

where the first letter denotes one aspect of the distribution that it refers to:
D = density function (density)
p = Distribution functions (distribution function)
Q = number of decimal functions (quantile function)
R = Generate random number (random deviation)
Common probability functions are shown in the following table:

Table 1 Probability distributions

Distribution Name	Abbreviation	Distribution Name	Abbreviation
Beta distribution	Beta	Logistic distribution	Logis
Two item distributions	Binom	Multi-item Distribution	Multinom
Cauchy distribution	Cauchy	Negative two-item distribution	Nbinom
(non-center) Chi-square distribution	Chisq	Normal	Norm
Exponential distribution	Exp	Poisson distribution	POIs
F Distribution	F	Wilcoxon symbol Rank Distribution	Signrank
Gamma distribution	Gamma	T distribution	T
Geometric distribution	Geom	Evenly distributed	Unif
Super Geometric distribution	Hyper	Weibull distribution	Weibull
Logarithmic normal distribution	Lnorm	Wilcoxon Rank and distribution	Wilcox

If you do not specify a mean and a standard deviation, the function assumes that it is a standard normal distribution (the mean value is 0 and the standard deviation is 1). The density function (dnorm), the distribution function (Pnorm), the Division function (Qnorm), and the random number generation function (Rnorm).

Reference:

[1] [Beauty]robert I. Kabacoff,r language Practice (R in Action Data analysis and Graphics with R)

R language Learning Note-probability function