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SSJ V. 1.2.5. |
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StatProbe
,
for collecting statistics on a
variable that evolves in simulation time, with a piecewise-constant trajectory.activeTests
, formatActiveTests
, etc.
tests
, then computes the p-values of those
that currently belong to activeTests,
and return these quantities in sVal and pVal, respectively.
add
, but adds the new event ev
immediately after the event other in the list.
add
, but adds the new event ev
immediately before the event other in the list.
addRandomShift
(0, dim, stream),
where dim is the dimension of the digital net.
FDist.andersonDarling
(n, x).
RandomStream
to
return antithetic variates.s
static method to append str to the buffer.
f
static method to append x to the buffer.
f
static method to append x to the buffer.
d
static method to append x to the buffer.
d
static method to append x to the buffer.
format
static method with the same four arguments to append x to the buffer.
RandomStream
.barF
(alpha, beta, 0, 1, d, x).
barF
(alpha, beta, d, x).
barF
(alpha, 1.0, d, x).
NormalDist.barF01
.
barF
(0.0, 1.0, x).
barF
(0.0, 1.0, x).
RandomStream
implementation via the
newInstance
method.ContinuousDistribution
for
the beta distribution with shape parameters
α > 0 and β > 0, over the interval (a, b), where a < b.BetaRejectionLoglogisticGen
(s, s, dist).
BetaStratifiedRejectionGen
(s, s, dist).
BetaDist
to the case of a symmetrical
beta distribution over the interval [0, 1],
with shape parameters
α = β.EventList
using a binary search tree.DiscreteDistributionInt
for the
binomial distribution with parameters n and p, where
n is a positive integer and
0 <= p <= 1.ContinuousDistribution2Dim
for the bivariate
normal distribution.BiNormalDist
for the bivariate
normal distribution
using a translation of Donnelly's FORTRAN code.BiNormalDonnellyDist
(rho, 15).
BiNormalDonnellyDist
(mu1, sigma1, mu2, sigma2, rho, 15).
BiNormalDist
for the bivariate
normal distribution
using Genz's algorithm as described in.ContinuousDistribution2Dim
for the standard bivariate Student's t distribution.ContinuousDistribution
for
the Cauchy distribution
with location parameter α
and scale parameter β > 0.cdf
(alpha, beta, 0, 1, d, x).
cdf
(alpha, alpha, d, x).
cdf01
.
cdf
(0.0, 1.0, x).
cdf
(0.0, 1.0, x).
chi2
,
except that the expected
number of observations per category is assumed to be the same for
all categories, and equal to nbExp.
ContinuousDistribution
for the chi
distribution with shape parameter
v > 0, where the number of degrees of freedom
v is a positive integer.ContinuousDistribution
for
the chi-square distribution with n degrees of freedom,
where n is a positive integer.ChiSquareDist
with
faster but less accurate methods.ChronoSingleThread
class extends the Chrono
class and computes
the CPU time for the current thread only.connectToDatabase
(new FileInputStream (file)).
connectToDatabase
(new FileInputStream (fileName)).
connectToDatabase
with the stream obtained from
the resource resource.
FDist.cramerVonMises
(n, x).
CycleBasedPointSet
, except that the successive
values in the cycles are stored as integers in the range
{0,..., 2k -1}, where
1 <= k <= 31.d
(0, 1, x).
d
(fieldwidth, 1, x).
density
(alpha, beta, 0, 1, x).
UnsupportedOperationException
if a or b are infinite.
diff
for the continuous case.
DigitalNet
for the base b = 2.DigitalNetBase2FromFile
(filename, r, 31, s1) where
s1 is the dimension and r is given in data file filename.
DigitalNetFromFile
(filename, r, r, s) where
s is the dimension and r is given in data file filename.
ContinuousDistributionMulti
for the
Dirichlet distribution with parameters
(α1,...,αd),
αi > 0.RandomMultiVariateGen
for a
Dirichlet distribution.EventList
using a doubly linked linear list.E
(0, 6, x).
E
(fieldwidth, 6, x).
e
(0, 6, x).
e
(fieldwidth, 6, x).
DiscreteDistribution
to an empirical
distribution function,
based on the observations
X(1),..., X(n) (sorted by increasing order).formatp0
to determine
which p-values are too close to 0 or 1 to be printed explicitly.
GammaDist
for the special case
of the Erlang distribution with
shape parameter k > 0 and scale parameter
λ > 0.interpol
(n, X, Y, C),
this function returns the value of the interpolating polynomial evaluated at z.
actions
method.
ContinuousDistribution
for
the exponential distribution
with mean 1/λ where
λ > 0.ContinuousDistribution
for
the extreme value (or Gumbel) distribution, with location parameter
α and scale parameter
λ > 0.f
(0, 6, x).
f
(fieldwidth, 6, x).
RandomStream
interface by using as a backbone
generator the combination of the WELL607 proposed in
(and implemented in WELL607
) with a nonlinear generator.F2wNetLFSR
,
F2wNetPolyLCG
,
F2wCycleBasedLFSR
and
F2wCycleBasedPolyLCG
.ContinuousDistribution
for
the Fatigue Life distribution with location
parameter μ, scale parameter β and shape
parameter γ.FaureSequence
(b, k, w, w, dim)
with base b equal to the smallest prime larger or equal to dim,
and with at least n points.
FDist
, except that it provides static methods
to compute or approximate the complementary distribution function of X,
which we define as
bar(F)(x) = P[X >= x], instead of
F(x) = P[X <= x].ContinuousDistribution
for
the Fisher F-distribution with n and m
degrees of freedom, where n and m are positive integers.init
for this Chrono to a String
in
the HH:MM:SS.xx format.
String
in the HH:MM:SS.xx format.
d
(0, 1, x).
String
with a minimum length
of fieldwidth, the result is right-padded with spaces if
necessary but it is not truncated.
String
containing x.
String
containing the elements n1
to n2 (inclusive) of table V,
k elements per line, p positions per element.
formatBase
(0, b, x).
String
representation in base
b.
formatConfidenceIntervalStudent
.
formatConfidenceIntervalStudent
.
confidenceIntervalStudent
,
but returns the confidence interval in a formatted string of the form
``95% confidence interval for mean: (32.431, 32.487)'',
using d decimal digits of accuracy.
formatKS
,
but for the KS statistic DN+(a).
formatKS
,
but for DN+(a).
formatp0
to print p, and adds
the marker ``****'' if p is considered suspect
(uses the environment variable RSUSPECTP for this).
formatp1
.
formatPoints
with n and d equal to the
number of points and the dimension, respectively.
toString
, together with the first d coordinates of the
first n points.
G
(0, 6, x).
G
(fieldwidth, 6, x).
g
(0, 6, x).
g
(fieldwidth, 6, x).
ContinuousDistribution
for
the gamma distribution with
shape parameter
α > 0 and scale parameter
λ > 0.RandomStream
interface via inheritance
from RandomStreamBase
.DiscreteDistributionInt
for
the geometric distribution with parameter
p, where 0 < p < 1.DoubleArrayList
object that contains the observations for this probe.
StringBuffer
associated with that object.
ContinuousDistribution
object by executing the code contained in the string str.
getContinuousDistribution
, but for discrete distributions
over the real numbers.
getContinuousDistribution
, but for discrete distributions
over the integers.
ContinuousDistribution
object by estimating parameters of the distribution using the maximum likelihood
method based on the n observations in table x[i],
i = 0, 1,…, n - 1.
DiscreteDistributionInt
object by estimating parameters of the distribution using the maximum likelihood
method based on the n observations in table x[i],
i = 0, 1,…, n - 1.
ContinuousDistribution
object by estimating parameters of the distribution using the maximum likelihood
method based on the n observations in table x[i],
i = 0, 1,…, n - 1.
DiscreteDistributionInt
object by estimating parameters of the distribution using the maximum likelihood
method based on the n observations in table x[i],
i = 0, 1,…, n - 1.
Distribution
used by this generator.
RandomVariateGen
used by this object.
init
for this Chrono.
update
method (or the initial value if
update
was never called after init
).
init
for this Chrono.
init
for this Chrono.
RandomStream
used by this generator.
RandomStream
used by this object.
UnsupportedOperationException
if a or b are infinite.
String
.
EventList
using the doubly-linked
index list of Henriksen.ContinuousDistribution
for
the Hyperbolic Secant distribution with location
parameter μ and scale parameter
σ > 0.DiscreteDistributionInt
for
the hypergeometric distribution with
k elements chosen among l, m being
of one type, and l - m of the other.iBinomialMatrixScramble
except that the diagonal
elements of each matrix
Mj are chosen as in
leftMatrixScrambleFaurePermut
.
iBinomialMatrixScrambleFaurePermut
except that the
elements under the diagonal are also
chosen from the same restricted set as the diagonal elements.
iBinomialMatrixScrambleFaurePermut
except that all the
off-diagonal elements are 0.
init
followed by update
(x).
init
, but also chooses evlist as the
event list to be used.
setStatCollecting
(true) and makes an update for the
probe on the list size.
inverseF
(alpha, beta, 0, 1, d, u).
inverseF
(alpha, 1, d, u).
NormalDist.inverseF01
.
inverseF
(0.0, 1.0, u).
inverseF
(0.0, 1.0, u).
ContinuousDistribution
for
the inverse Gaussian distribution with location parameter
μ > 0 and scale parameter
λ > 0.iterator
, except that the first coordinate
of the points is i/n, the second coordinate is obtained via
the generating matrix
C0, the next one via
C1,
and so on.
iterator
, except that the first coordinate
of the points is i/n, the second coordinate is obtained via
the generating matrix
C0, the next one via
C1,
and so on.
iterSpacingsTests
, but with the
GofStat.powerRatios
transformation.
GofStat.iterateSpacings
transformation to the
U(0),..., U(N-1), assuming that these observations are in
sortedData, then computes the EDF test statistics and calls
activeTests
after each transformation.
ContinuousDistribution
for
the Johnson SB distribution
with shape parameters γ and
δ > 0, location parameter ξ,
and scale parameter λ > 0.ContinuousDistribution
for
the Johnson SU distribution.JohnsonSUDist
(gamma, delta, 0.0, 1.0).
KernelDensityGen
, but with
a rescaling of the empirical distribution so that the variance
of the density used to generate the random variates is equal
to the empirical variance,
as suggested by Silverman.FDist.kolmogorovSmirnov
(n, x).
FDist.kolmogorovSmirnovPlusJumpOne
, assuming that F is the
uniform distribution over [0, 1] and that
U(1),..., U(N) are in sortedData.
FDist.kolmogorovSmirnovPlus
(n, x).
kolmogorovSmirnovPlus
but for the case where the distribution
function F has a jump of size a at a given point x0,
is zero at the left of x0,
and is continuous at the right of x0.
LCGPointSet
, but implemented differently.ContinuousDistribution
for
the Laplace distribution.leftMatrixScramble
except that all the
off-diagonal elements of the
Mj are 0.
leftMatrixScramble
except that the diagonal elements
of each matrix
Mj are chosen from a restricted set of the best
integers as calculated by Faure.
leftMatrixScrambleFaurePermut
except that the
elements under the diagonal are also
chosen from the same restricted set as the diagonal elements.
leftMatrixScrambleFaurePermut
except that all
off-diagonal elements are 0.
RandomStreamBase
using a composite linear feedback
shift register (LFSR) (or Tausworthe) RNG as defined in.RandomStreamBase
using a 64-bit composite linear feedback
shift register (LFSR) (or Tausworthe) RNG as defined in.LinkedList
, with statistical
probes integrated in the class to provide automatic collection of
statistics on the sojourn times of objects in the list and the
size of the list as a function of time.DiscreteDistributionInt
for
the logarithmic distribution.ContinuousDistribution
for the
logistic distribution.ContinuousDistribution
for the
Log-Logistic distribution with shape parameter
α > 0
and scale parameter β > 0.ContinuousDistribution
for the
lognormal distribution.matMatModM
using double, but with int instead
of double.
matMatModM
using double, but with long instead
of double.
matPowModM
using double, but with int instead
of double.
matPowModM
using double, but with long instead
of double.
matTwoPowModM
using double, but with int instead of
double.
matTwoPowModM
using double, but with long instead of
double.
matVecModM
using double, but with int instead
of double.
matVecModM
using double, but with long instead
of double.
RandomStreamBase
, thus
implementing the RandomStream
interface indirectly.RandomStreamBase
by using as a
backbone (or main) generator the combined multiple recursive
generator (CMRG) MRG32k3a proposed by L'Ecuyer,
implemented in 64-bit floating-point arithmetic.RandomStream
interface via inheritance from
RandomStreamBase
.DiscreteDistributionIntMulti
for the
multinomial distribution with parameters n and
(p1, ...,pd).ContinuousDistributionMulti
for the
multinormal distribution with mean vector μ and covariance
matrix Σ.RandomMultiVariateGen
for a
multivariate normal distribution.MultiNormalGen
(gen1, mu, new DenseDoubleMatrix2D (sigma)).
BitVector
by a BitMatrix
and returns the result.
BitVector
, by
a BitMatrix.
DiscreteDistributionInt
for
the negative binomial distribution with real
parameters γ and p, where
γ > 0 and
0 <= p <= 1.DiscreteDistributionIntMulti
for the
negative multinomial distribution with parameters
γ > 0 and
(p1,...,pd).nextDouble
(s, s, alpha, lambda).
nextDouble
(in which the baker transformation is applied).
nextPoint
(gen1, mu, new DenseDoubleMatrix2D (sigma), p).
ContinuousDistribution
for the normal
distribution (e.g.,).NormalDist
(for the normal
distribution with mean μ and variance σ2).ContinuousDistribution
for a distribution
from the Pareto family, with
shape parameter
α > 0 and location parameter β > 0.ContinuousDistribution
for
the Pearson type V distribution with shape parameter
α > 0 and scale parameter β > 0.ContinuousDistribution
for
the Pearson type VI distribution with shape parameters
α1 > 0 and
α2 > 0, and scale parameter β > 0.ContinuousDistribution
for a piecewise-linear
approximation of the empirical distribution function,
based on the observations
X(1),..., X(n) (sorted by increasing order),
and defined as follows (e.g.,).DiscreteDistributionInt
for the
Poisson distribution with mean
λ >= 0.PoissonGen
).String
containing all the data of
the BitMatrix.
StringBuffer
which defines new types
of append methods.RandomVariateGen
and RandomVariateGenInt
instead.newInstance
method
each time a new random stream is needed, instead of invoking
directly the specific constructor of the desired type.newInstance
method.Rank1Lattice
with n points and lattice
vector a of dimension s.
readDoubleData
to
obtain an array of double-precision values from
the file.
readDoubleData
to
obtain an array of double-precision values from
the file.
readDoubleData2D
to
obtain a matrix of double-precision values from
the file.
readDoubleData2D
to
obtain a matrix of double-precision values from
the file.
readDoubleData
,
for reading integers.
readDoubleData
,
for reading integers.
readDoubleData
,
for reading integers.
readDoubleData2D
,
for reading integers.
readDoubleData2D
,
for reading integers.
readDoubleData2D
,
for reading integers.
EventList
using a red black tree,
which is similar to a binary search tree except that
every node is colored red or black.simprocs
;
it should not be used directly by a simulation program.
setStatCollecting
(true) has been
called before for this list.
reportAndConfidenceIntervalStudent
.
reportAndConfidenceIntervalStudent
.
report
), followed by a confidence interval
(as in formatConfidenceIntervalStudent
),
using d decimal digits of accuracy.
reportAndConfidenceIntervalStudent
(level, 3).
setCurCoordIndex
(0).
setCurPointIndex
(0).
resetNextSubstream
methods
of all streams in the list.
resetStartStream
methods
of all streams in the list.
resetStartSubstream
methods
of all streams in the list.
AbstractSimProcess
objects.s
(0, str).
FBar.scan
.
UserRecord
objects
for the processes in the service list for this resource.
nextDouble
.
nextDouble
.
nextCoordinate
or nextCoordinates
will return the values
ui, j, ui, j+1,..., where i is the
index of the current point.
RandomVariateGen
used by this object to gen1.
waitList
for this bin.
waitList
and servList
for this resource.
RandomStream
used by this generator to stream.
RandomStream
used by this object to stream.
EventList
using a splay tree.startInteg
, after initializing the variable
to val.
UserRecord
for this resource.
start
.
stripedMatrixScramble
except that the
elements on and under the diagonal of each matrix
Mj are
chosen as in leftMatrixScrambleFaurePermut
.
ContinuousDistribution
for
the Student-t distribution
with n degrees of freedom, where n is a positive integer.PointSet
object, initially identical to P,
and from which a subset of the points and/or a subset of the coordinates
is to be extracted.
formatp1
to determine
which p-values should be marked as suspect when printing test results.
String
s in different styles.Tally
, but for which the individual
observations are stored in a list implemented as a
DoubleArrayList
.String
containing all the data of
the BitMatrix.
String
.
ContinuousDistribution
for
the triangular distribution with domain [a, b] and mode
(or shape parameter) m, where
a <= m <= b.ContinuousDistribution
for
the uniform distribution
over the interval [a, b].DiscreteDistributionInt
for
the discrete uniform distribution over the range [i, j].UnuranContinuous
(s, s, genStr).
UnuranDiscreteInt
(s, s, genStr).
UnuranEmpirical
(s, s, dist, genStr).
UnuranEmpirical
(s, aux, genStr), but reading
the observations from the empirical distribution dist.
update
.
Resource
or for Bin
tokens,
or when a process waits for a Condition
.UserRecord
for the processes waiting for tokens from this bin.
UserRecord
for the processes waiting for this condition.
UserRecord
objects
for the processes in the waiting list for this resource.
FDist.watsonG
(n, x).
watsonU
,
for a sample of independent uniforms over (0, 1).
FDist.watsonU
(n, x).
ContinuousDistribution
for
the Weibull distribution with shape parameter
α > 0, location parameter δ, and scale parameter
λ > 0.RandomStream
interface via inheritance from
RandomStreamBase
.RandomStream
interface via inheritance from
RandomStreamBase
.RandomStream
interface via inheritance
from RandomStreamBase
.
|
SSJ V. 1.2.5. |
||||||||
PREV NEXT | FRAMES NO FRAMES |