# Td-class

From distr v1.4
0th

Percentile

##### Class "Td"

The $t$ distribution with df $= \nu$ degrees of freedom has density $$f(x) = \frac{\Gamma ((\nu+1)/2)}{\sqrt{\pi \nu} \Gamma (\nu/2)} (1 + x^2/\nu)^{-(\nu+1)/2}$$ for all real $x$. It has mean $0$ (for $\nu > 1$) and variance $\frac{\nu}{\nu-2}$ (for $\nu > 2$). C.f. rt

##### Note

The general non-central $t$ with parameters $(\nu,\delta)$ = (df, ncp) is defined as a the distribution of $T_{\nu}(\delta) := \frac{U + \delta}{\chi_{\nu}/\sqrt{\nu}}$ where $U$ and $\chi_{\nu}$ are independent random variables, $U \sim {\cal N}(0,1)$, and $\chi^2_\nu$ is chi-squared, see pchisq.

The most used applications are power calculations for $t$-tests: Let $T= \frac{\bar{X} - \mu_0}{S/\sqrt{n}}$ where $\bar{X}$ is the mean and $S$ the sample standard deviation (sd) of $X_1,X_2,\dots,X_n$ which are i.i.d. $N(\mu,\sigma^2)$. Then $T$ is distributed as non-centrally $t$ with df$= n-1$ degrees of freedom and non-centrality parameter ncp$= (\mu - \mu_0) \sqrt{n}/\sigma$.

class

##### Objects from the Class

Objects can be created by calls of the form Td(df). This object is a $t$ distribution.

##### Extends

Class "AbscontDistribution", directly. Class "UnivariateDistribution", by class "AbscontDistribution". Class "Distribution", by class "AbscontDistribution".

##### See Also

TParameter-class AbscontDistribution-class Reals-class rt

##### Aliases
• Td-class
• Td
• initialize,Td-method
##### Examples
T <- Td(df = 1) # T is a t distribution with df = 1.
r(T)(1) # one random number generated from this distribution, e.g. -0.09697573
d(T)(1) # Density of this distribution is 0.1591549 for x = 1.
p(T)(1) # Probability that x < 1 is 0.75.
q(T)(.1) # Probability that x < -3.077684 is 0.1.
df(T) # df of this distribution is 1.
df(T) <- 2 # df of this distribution is now 2.
Documentation reproduced from package distr, version 1.4, License: GPL (version 2 or later)

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