|
SSJ V. 2.5. |
||||||||
| PREV NEXT | FRAMES NO FRAMES | ||||||||
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.
andersonDarling).
ContinuousDistribution for the
Anderson-Darling distribution (see).AndersonDarlingDist for the
distribution (see).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.
isDouble.
isFloat.
isInt.
average, and stores
the results into the array a.
RandomStream.barF (alpha, beta, 0, 1, d, x).
barF (alpha, 1.0, d, x).
NormalDist.barF01.
barF (0, 1, x).
barF (0.0, 1.0, x).
RandomStream implementation via the
newInstance method.DiscreteDistributionInt for the Bernoulli
distribution with parameter p, where
0 <= p <= 1.BernoulliDist).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.CategoryChart.close.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).
GumbelDist.
cdf01.
cdf (0, 1, 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.ContinuousDistribution for
the noncentral chi-square distribution with ν degrees of freedom
and noncentrality parameter λ, where ν > 0 and
λ > 0.Chrono class extends the
AbstractChrono
class and computes the CPU time for the current thread only.CloneableRandomStream extends RandomStream and Cloneable.computeDensity ,
but the bandwidth h is obtained from the method
KernelDensityGen.getBaseBandwidth(dist) in package randvar.
connectToDatabase (url.openStream()).
connectToDatabase (new FileInputStream (file)).
connectToDatabase (new FileInputStream (fileName)).
connectToDatabase with the stream obtained from
the resource resource.
DiscreteDistribution for a constant
discrete distribution taking a single real value with probability 1.UniformIntDist for a constant
discrete distribution taking a single integer value with probability 1.covariance for computing
the sample correlation matrix.
ContinuousDistribution for the
Cramér-von Mises distribution (see).Event object used for synchronization.
Tally.
Tally.
TallyStore.
TallyStore.
HistogramType.FREQUENCY.
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).
DataReader.Sim, and the no-argument constructor of Event.
density (alpha, beta, 0, 1, x).
density (0, 1, x).
diff(IntArrayList,IntArrayList,int,int,int,int),
but 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.DiscreteDistribution(double[], double[], int).
Comparator which compares two
double arrays by comparing their i-th element,
where i is given in the constructor.EventList using a doubly linked linear list.String.
String.
E (0, 6, x).
E (fieldwidth, 6, x).
e (0, 6, x).
e (fieldwidth, 6, x).
TallyStore object.
DiscreteDistribution to an empirical
distribution function,
based on the observations
X(1),..., X(n) (sorted by increasing order).PointSetRandomization.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 P(z) evaluated
at z (see eq.
actions method.
exp(A).
ContinuousDistribution for
the exponential distribution
with mean 1/λ where
λ > 0.ExponentialDist class with a constructor accepting as
argument the mean 1/λ instead of the rate λ.GumbelDist.
GumbelDist.
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 n1 and n2
degrees of freedom, where n1 and n2 are positive integers.ContinuousDistribution for
the folded normal distribution with
parameters μ >= 0 and
σ > 0.init for this AbstractChrono 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.
format, except it formats the given
value for the locale locale.
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.
confidenceIntervalNormal.
confidenceIntervalStudent.
confidenceIntervalVarianceChi2.
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(n, d) with n and d equal to the
number of points and the dimension of this object, respectively.
toString, together with the first d coordinates of the
first n points.
formatPoints(iter, n, d)
with n and d equal to the number of points and the dimension, respectively.
formatPoints(n, d), but
prints the points by calling iter repeatedly.
formatPoints(), but the
points coordinates are printed in base b.
formatPoints(n, d), but the
points coordinates are printed in base b.
formatPoints(iter),
but the points coordinates are printed in base b.
formatPoints(iter, n, d),
but the points coordinates are printed in base b.
formatPointsNumbered(n, d)
with n and d equal to the number of points and the dimension,
respectively.
formatPoints(n,d), except that the points are numbered.
formatWithError,
except that it formats the given value and error for the
locale locale.
formatWithError,
except that it formats the given value and error for the
locale locale.
ContinuousDistribution for the Fréchet
distribution, with location parameter δ, scale
parameter β > 0, and shape parameter
α > 0, where we use
the notation
z = (x - δ)/β.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.GammaDist distribution with constructors accepting the
mean μ and variance σ2 as arguments instead of a shape parameter
α and a scale parameter λ.GammaProcessPCA, but the generated uniforms
correspond to a bridge transformation of the BrownianMotionPCA
instead of a sequential transformation.GammaProcessPCABridge, but uses the fast inversion method
for the symmetrical beta distribution, proposed by L'Ecuyer and Simard, to accelerate the generation of the beta random variables.gaussLobatto(MathFunction, double, double, double), but
also returns in T[0] the subintervals of integration, and in
T[1], the partial values of the integral over the corresponding
subintervals.
RandomStream's.
RandomStream interface via inheritance
from RandomStreamBase.BrownianMotion.
DiscreteDistributionInt for
the geometric distribution with parameter
p, where 0 < p < 1.BrownianMotionPCA that is included in the
GammaProcessPCA object.
BrownianMotionPCA.
BrownianMotion object
used to generate the process.
BrownianMotion.
BrownianMotionPCA.
StringBuffer associated with that object.
ContinuousDistribution
object by executing the code contained in the string str.
Sim.
getContinuousDistribution, but for discrete distributions
over the real numbers.
getContinuousDistribution, but for discrete distributions
over the integers.
Distribution used by this generator.
DiscreteDistributionInt used by this generator.
DoubleArrayList
object that contains the observations for this probe.
getField,
except that it can return non-public fields.
Polynomial instance used to evaluate
x, in an ArrayList table instance returned by
getSplinePolynomials().
GammaProcess.
NormalGen used.
GammaProcess object gneg
used to generate the
Γ- component of the process.
GammaProcess object gpos
used to generate the
Γ+ component of the process.
init for this AbstractChrono.
initStat was called.
getInstanceFromMLE, but for the case β < 0.
update method (or the initial value if
update was never called after init).
getMethod, except that it can return non-public methods.
init for this AbstractChrono.
getMLE, but for the case β < 0.
getLambda.
init for this AbstractChrono.
RandomStream.
RandomStream.
RandomStream.
RandomStream.
RandomStream used by this generator.
RandomStream used by this object.
RandomStream stream.
RandomStream
for the underlying Brownian motion.
RandomStream's are the same.
InverseGaussianProcess.
BrownianMotion process, which should
be the same as for the GammaProcess.
evaluate in the
case where the 0/0 function is calculated.
AbstractChrono class to compute the global CPU time used
by the Java Virtual Machine.