# internals_for_distr

##### Internal functions of package distr

These functions are used internally by package distr.

- Keywords
- internal

##### Usage

```
.is.vector.lattice(x)
.is.consistent(lattice, support, eq.space = TRUE)
.make.lattice.es.vector(x)
.inArgs(arg, fct)
.isEqual(p0, p1, tol = min( getdistrOption("TruncQuantile")/2,
.Machine$double.eps^.7))
.isEqual01(x)
.isIn(p0, pmat, tol = min( getdistrOption("TruncQuantile")/2,
.Machine$double.eps^.7
))
.isInteger(x, tol = .Machine$double.eps)
.isNatural(x, tol = .Machine$double.eps)
.isNatural0(x, tol = .Machine$double.eps)
.setEqual(x, y, tol = 1e-7)
.presubs(inp, frompat, topat)
.makeD(object, argList, stand = NULL, fac = NULL)
.makeP(object, argList, sign = TRUE, correct = NULL, fac =
NULL, fac2 = NULL)
.makeQ(object, lastCall, sign = TRUE, Cont = TRUE)
.plusm(e1, e2, Dclass = "DiscreteDistribution")
.multm(e1, e2, Dclass = "DiscreteDistribution")
.notwithLArg(D)
.getObjName(i = 1)
.discretizeP(D, lower, upper, h)
.fm(x,f)
.fM(x,f)
.fM2(x,f)
.makeDd(x,y, yleft, yright)
.makePd(x,y, yleft, yright)
.makeQd(x,y, yleft, yright)
.makeQc(x,y, yleft, yright)
.makeDNew(x, dx, h = NULL, Cont = TRUE, standM = "sum")
.makePNew(x, dx, h = NULL, notwithLLarg = FALSE,
Cont = TRUE, myPf = NULL, pxl = NULL, pxu = NULL)
.makeQNew(x, px.l, px.u, notwithLLarg = FALSE, yL , yR, Cont = TRUE)
.mergegaps(gaps, support)
.mergegaps2(gaps1, gaps2)
.pmixfun(mixDistr, mixCoeff)
.dmixfun(mixDistr, mixCoeff, withStand = FALSE, supp = NULL)
.rmixfun(mixDistr, mixCoeff)
.qmixfun(mixDistr, mixCoeff, Cont = TRUE, pnew)
.del0dmixfun(mixDistr)
.loupmixfun(mixDistr)
.expm.d(e1)
.expm.c(e1)
.logm.d(e1)
.logm.c(e1)
.P2D (p, xx, ql, qu, ngrid = getdistrOption("DefaultNrGridPoints"))
.P2Q (p, xx, ql,qu, ngrid = getdistrOption("DefaultNrGridPoints"),
qL = -Inf, qU = Inf)
.D2P (d, xx, ql, qu, ngrid = getdistrOption("DefaultNrGridPoints"))
.Q2P (q, ngrid = getdistrOption("DefaultNrGridPoints"))
.csimpsum(fx)
.primefun(f,x, nm = NULL)
.IssueWarn(Arith,Sim)
devNew(...)
```

##### Arguments

- x
- a (numeric) vector
- y
- a (numeric) vector
- f
- a function in one (numeric) argument
- lattice
- a lattice (of class
`Lattice`

) - support
- a support vector
- eq.space
- logical: shall we check for the support to be equally spaced?
- arg
- a formal argument as character
- fct
- a function
- p0,p1
- (numeric) vectors
- pmat
- (matrix) a matrix with two columns where row-wise the left column is smaller than the right one
- tol
- an error tolerance (numeric)
- e1
- a distribution object
- e2
- a numeric
- object
- a distribution object
- argList
- an (unevaluated) list of arguments passed to
`m(object)`

where`m`

is in`d,p,q`

- stand
- factor for a (Lebesgue) density to integrate to 1
- sign
- the sign of the second operand --- for multiplication at the moment
- correct
- unevaluated R-code to correct for right-continuity (for multiplication with negative numerics at the moment)
- fac
- factor to be multiplied with the return value
- fac2
- factor to be added to the return value
- lastCall
- unevaluated R-Code ---gives how the result of a call to
`q(e1)`

is further transformed - Cont
- logical:
`TRUE`

if`object`

is continuous - DClass
- character: name of distribution class
- D
- a distribution object
- i
- an integer
- yleft, yright
- extrapolation value beyond left/right endpoint of grid
- h
- numeric: grid width
- standM
- standardization method --- summation or integration
- notwithLLarg
- logical --- can we use
`log.p`

,`lower.tail`

arguments for`p,q`

-methods of first operand? - dx
- numeric: vector of cell-probabilities for the (discretized) distribution
- myPf
- function with args
`x,y, yleft, yright`

(as`approxfun`

): if given: replaces`approxfun`

as interpolation method for continuos distributions - pxl,pxu
- numeric: if given vector of (lower/upper) cumulative probabilities
- yL, yR
- argmin / argmax of p()-method
- inp
- either a language object or a character vector
- frompat
- vector of character strings containing regular expressions (or
character string for
`fixed = TRUE`

) to be matched in the given character vector. Coerced by`as.character`

to a character string if pos - topat
- a (vector of) replacement(s) for matched pattern in
`.presubs`

. Coerced to character if possible. For`fixed = FALSE`

this can include backreferences`"\1"`

to`"\9"`

to - gaps,gaps1,gaps2
- matrices
`m`

with two columns, such that`t(m)`

, interpreted as vector, is ordered - support
- support vector of a univariate discrete distribution
- mixDistr
- an object of class
`UnivarDistrList`

- mixCoeff
- an object of class
`numeric`

; a probability vector - pnew
- a function
`function(q, lower.tail = TRUE, log.p = FALSE`

realizing slot`p`

in a distribution object. - withStand
- logical; if
`TRUE`

a standardization is made such that the sum of the values of the result evaluated at argument`supp`

is 1 - supp
- NULL or
`numeric`

; if`withStand`

is`TRUE`

used to standardize such that the result is a probability density. - p
- slot
`p`

of an object of class`"AbscontDistribution"`

- d
- slot
`d`

of an object of class`"AbscontDistribution"`

- q
- slot
`q`

of an object of class`"AbscontDistribution"`

- xx
- a given grid of x-values for functions
`p`

,`d`

to be evaluated at - ql,qu
- lower and upper
`getdistrOption("TruncQuantile")`

-quantile of the distribution; also, if argument`xx`

is missing, left and right endpoint of a regular grid of`ngrid`

gridpoints to be used in place of`xx`

. - qL,qU
- argmin / argmax of p()-method
- ngrid
- number of gridpoints
- fx
- a vector of function evaluations multiplied by the gridwidth
- f
- a vector of function evaluations
- nm
- an optional right asymptotic value
- Arith
- logical; slot
`.withArith`

of a distribution object, or logically-``any'' of these slots in a collection of such objects - Sim
- logical; slot
`.withSim`

of a distribution object, or logically-``any'' of these slots in a collection of such objects - ...
- arguments passed through to other functions

##### Details

`.is.vector.lattice`

checks whether a given vector `x`

is equally
spaced.
`.is.consistent`

checks whether a given support vector `support`

is
consistent to a given lattice `lattice`

--- with or without checking
if `support`

is equally spaced. `.make.lattice.es.vector`

makes an object of class `Lattice`

out of a given (equally spaced) vector
`x`

.
`.inArgs`

checks whether an argument `arg`

is a formal argument of
`fct`

--- not vectorized.
`.isEqual`

checks whether `p0`

and `p1`

are equal to given
tolerance.
`.isIn`

checks whether `p0`

lies in any of the intervals given by
matrix `pmat`

to given tolerance.
`.isEqual01`

(x) checks whether `x`

is 0 or 1 to given tolerance.
`.setEqual`

sets all elements of x which are equal to some element of y
up to tolerance tol, to exactly the respective element of y.
`.notwithLArg`

checks whether object `D`

was generated by simulations
or if its slots `p,q`

do not have `lower.tail`

arguments.
`.getObjName`

returns the name of the object in the `i`

th operand.
`.discretizeP`

discretizes `D`

to a grid of probabilities from
`lower`

to `upper`

with width `h`

.
`.fm`

, `.fM`

return the smallest / biggest value in (0,1) such that
`f`

(x) is finite; `.fM2`

is a variant of `.fM`

using a
`lower.tail = FALSE`

argument.
`.makeD`

, `.makeP`

, `.makeQ`

generate slots `p,d,q`

for
binary operations `e1 /op/ e2`

for a distribution object `e1`

and a numeric `e2`

---for the moment only `/op/`

's
`+,-,*,/`

are implemented.
`.plusm`

, `.multm`

more specifically use `.makeD`

, `.makeP`

,
`.makeQ`

to generate slots `p,d,q`

for `+`

, `*`

,
respectively.
`.makeDd`

, `.makePd`

, `.makeQd`

provide discrete analogues to
`approxfun`

for interpolation at non grid-values
`.makeQc`

is an analogue to `makeQd`

for absolutely continuous
distributions using `approxfun`

.
`.makeDNew`

generates slot `d`

for a new distribution object.
In case of a discrete distribution it produces a step function with
`stepfun`

(using `.makeDd`

) and standardizes to 1 by summation.
In case of a continuous distribution it produces a density function with
`approxfun`

and standardizes to 1 by integration if the latter fails,
it uses a trapezoid rule / summation for this purpose.
`.makePNew`

generates slot `p`

for a new distribution object.
In case of a discrete distribution it produces a step function from
`cumsum`

applied to `dx`

---or from `pxl`

if this is given, with
`stepfun`

(using `.makePd`

).
In case of a continuous distribution it produces a cdf with
`approxfun`

. In case of `RtoDPQ`

, `approxfun`

is replaced by
`myPf`

which calls `ecdf`

directly.
`.makeQNew`

generates slot `q`

for a new distribution object.
In case of a discrete distribution it produces a step function
(using `.makeQd`

). Special care is taken for left continuity...
In case of a continuous distribution it produces a quantile function with
`approxfun`

.
`.isInteger`

, `.isNatural`

, and `.isNatural0`

test for each
coordinate of argument `x`

whether it
is integer [natural / natural or 0] or not.
`.mergegaps`

modifies the gaps matrix of an a.c. distribution according to
the support slot of a discrete distribution; if necessary, a gap interval
[a,b] is split into [a,c],[c,b] if `a`

`.mergegaps2`

merges two gap matrices of two a.c. distributions `X1`

and `X2`

such that in the intervals of the resulting gap matrix,
neither `X1`

nor `X2`

carries mass.
`.pmixfun`

, `.dmixfun`

, `.rmixfun`

, and `.qmixfun`

fill the slots `p`

, `d`

, `r`

, and `q`

of a corresponding mixing distribution according to the arguments
in `mixDistr`

, `mixCoeff`

.
`.loupmixfun`

finds commun lower and upper bounds for the support of
the mixing distribution.
`.del0dmixfun`

sets (if slot `d.ac`

is not `NULL`

) the return
value of slot function `d.ac`

of `mixDistr`

for argument `0`

to `0`

.
`.expm.d,.expm.c`

for discrete, resp. a.c. argument `e1`

fill the
slots `p`

, `d`

, `r`

, and `q`

of the transformation `exp(e1)`

exactly.
`.logm.d,.logm.c`

for discrete, resp. a.c. argument `e1`

fill the
slots `p`

, `d`

, `r`

, and `q`

of the transformation `log(e1)`

exactly.
For objects of class `AbscontDistribution`

,
`.P2D`

and `.P2Q`

reconstruct function slots `d`

resp.
`q`

from function slot `p`

by means of function `D1ss`

from package `.makeQNew`

, respectively. The other way round,
`.D2P`

and `.Q2P`

reconstruct function slot `p`

from
from function slots `d`

resp. `q`

by means of function `.makePNew`

and explicite numeric inversion,
respectively.
`.csimpsum`

is used internally in `.makePNew`

to produce
a primitive function out of function evaluations by means of vectorized
Simpson quadrature method, returning already the function values
of the prime function on a grid; it is to mimick the behaviour
of `cumsum`

. `.primefun`

is similar but more flexible and
produces the prime function as a function.
`devNew`

opens a new device. This function is for back compatibility
with R versions < 2.8.0.

##### Value

.is.vector.lattice `logical`

(length 1)..is.consistent `logical`

(length 1)..notwithLArg `logical`

(length 1)..make.lattice.es.vector an object of class `Lattice`

..inArgs `logical`

(length 1)..isIn, .isEqual,.isEqual01 vector of `logical`

..fm,.fM, .fM2 a `numeric`

of length 1..plusm,.multm an object of class `DiscreteDistribution`

or`AbscontDistribution`

according to argument`DClass`

..getObjName `character`

..discretizeP `numeric`

--- the probabilities for the grid-values..makeDd,.makePd, .makeQd a function with args `x, y, yleft, yright`

..makeD,.makeDNew a function with args `x, log = FALSE`

..makeP,.makePNew a function with args `q, lower.tail = TRUE, log.p = FALSE`

..makeQ,.makeQNew a function with args `p, lower.tail = TRUE, log.p = FALSE`

..isInteger,.isNatural,.isNatural0 `logical`

(same length as argument`x`

)..mergegaps,.mergegaps2 a `gaps`

-matrix, i.e.; a matrix`m`

with two columns, such that`t(m)`

, interpreted as vector, is ordered..pmixfun slot `p`

for a mixing distribution, i.e. a function`function(q, lower.tail = TRUE, log.p = FALSE)`

, which is the cdf of the distribution..dmixfun slot `d`

for a mixing distribution, i.e. a function`function(x, log = FALSE)`

, which is the density of the distribution..qmixfun slot `q`

for a mixing distribution, i.e. a function`function(p, lower.tail = TRUE, log.p = FALSE)`

, which is the quantile function of the distribution..rmixfun slot `r`

for a mixing distribution, i.e. a function`function(n)`

generating r.v.'s according to the distribution..deldmixfun a possibly modified argument `mixDistr`

..loupmixfun a list of four components: `qL`

, the minimal value of`q(x)(0)`

,`ql`

, the minimal value of`q(x)(getdistrOption("TruncQuantile"))`

,`qU`

, the maximal value of`q(x)(1)`

,`qu`

, the maximal value of`q(x)(getdistrOption("TruncQuantile"), lower.tail = FALSE)`

,`x`

running through the members of`mixDistr`

in each case..expm.d,.logm.d an object of class `"DiscreteDistribution"`

..expm.c,.logm.c an object of class `"AbscontDistribution"`

..P2D a density `d`

as function`function(x, log = FALSE)`

..P2Q a quantile function `q`

as function`function(p, lower.tail = TRUE, log.p = FALSE)`

.D2P, .Q2P a cdf `p`

as function`function(q, lower.tail = TRUE, log.p = FALSE)`

..csimpsum a vector of evaluations of the prime function at the grid points. .primefun the prime function as a function. .IssueWarn a list with two warnings to be issued each of which may be empty. devNew returns the return value of the device opened, usually invisible 'NULL'.

##### concept

utilities

##### See Also

`AbscontDistribution`

,
`DiscreteDistribution`

,
`LatticeDistribution`

,
`RtoDPQ`

,
`RtoDPQ.d`

,
`convpow`

,
`operators`

,
`plot-methods`

`dev.new`

*Documentation reproduced from package distr, version 2.0.6, License: LGPL-3*