

Neural
Nets 


Improved
calculation of the gradient. 



Optimization 


Resolved
buffer overrun issue. 



Error
Handling 


Exception
thrown when More's technique is not making any progress. 

Linear
Systems 


Returns
the lower triangular portion of the LU factorization of input matrix
"a". 


Returns
the the permutation matrix which results from the
LU factorization of input matrix "a". 


Returns
the unit upper triangular portion of the LU factorization of input matrix
"a". 


Returns
the lower triangular portion of the LU factorization of input matrix
"a". 


Returns
the the permutation matrix which results from the
LU factorization of input matrix "a". 


Returns
the unit upper triangular portion of the LU factorization of input matrix
"a". 

Optimization 


Solves
a nonlinear leastsquares problem subject to bounds on the variables using a
modified LevenbergMarquardt algorithm. This method
is the identical replacement for the deprecated method BoundedLeastSquares.solve.




Error
Handling 


Exception
thrown when More's technique is not making any progress. 



Changed
links to Microsoft SDK webpages for HTML documentation. 

Added
support for the FLEXLM_BATCH FlexNet environment
variable. This prevents popups from being displayed for FlexNet
errors/warnings. 

The
properties NumberOfProcessors and/or Parallel have
been added to many of the classes/methods which use the Task Parallel Library
in .NET 4.0. 



Added
TCB Spline to the Spline demo. 



General 

Corrected
problem with charts with axes on both the left and right side which resulted
in inconsistencies of the tick intervals and ticks which appear to be outside
the axis range. 



Linear
Systems 


Made
corrections so that the warning about a singular matrix is printed. 


Updated
class description with A = RR^{T}. 


Overloaded
method with processors argument. 


Overloaded
method with processors argument. 

Optimization 


Implemented
a fix for a potential infinite loop in More's technique. 


This
method has been deprecated and replaced by BoundedLeastSquares.Solve.



Updated
the documentation for the methods and properties SetXscale,
SetFscale, GradientTolerance,
and StepTolerance. 

Implemented
a fix for a potential infinite loop in More's technique. 


Modified
the write statement in Example 3. 



Regression 


Implemented
a fix for a potential infinite loop in More's technique. 

Probability
Distribution Functions and Inverses 


Corrected
an equation in the documentation. 


Enhanced
the documentation. 


Enhanced
the documentation. 


Enhanced
the documentation. 


Enhanced
the documentation. 


Enhanced
the documentation. 


Enhanced
the documentation. 

Random
Number Generation 

Added
description for the valid value of the seeds for the Random constructor. 


Changed
from a static public method to a static method. 


Overloaded
version using the k argument has been deprecated. 


Overloaded
version using the k argument has been deprecated. 


Overloaded
version using the k argument has been deprecated. 

Probability
Distribution Functions and Inverses 


A
new algorithm is used to improve accuracy in the tails of the distribution. 


Improved
performance. 

Time
Series and Forecasting 


Removed
extra terms from the difference equation in the documentation. 

Implemented
a fix for a potential infinite loop in More's technique. 




Error
Handling 



Logs
intermediate results and notes from IMSL C# classes. 



Signals
that an unexpected error has occurred. 



Throws
an 





Linear
Systems 



Returns
the inverse of the lower triangular matrix 



Returns
the inverse of the upper triangular matrix 


Eigensystems Analysis 



A
constructor was added. 



Set
or returns the maximum number of iterations. 



Solves
for the eigenvalues and (optionally) the eigenvectors of a real square
matrix. 


Interpolation
and Approximation 



Extension
of the Spline class to handle a tensioncontinuitybias (TCB) cubic spline,
also known as a KochanekBartels spline and is a
generalization of the CatmullRom spline. 



Returns
the value of an integral of a tensorproduct spline on a rectangular domain. 



Computes
a twodimensional, tensorproduct spline approximant using least squares. 


Differential
Equations 



ODE
represents and solves an initialvalue problem for ordinary differential
equations. 



Solves
the generalized FeynmanKac PDE. 



Extension
of the ODE class to solve a stiff initialvalue problem for ordinary
differential equations using the AdamsGear methods. 


Nonlinear
Equations 



Finds
the real zeros of a real, continuous, univariate function, f(x). 



Returns
the logger object. 


Optimization 



Solve
a linear leastsquares problem with bounds on the variables. 



Solves
a linear least squares problem with nonnegativity
constraints. 



Compute
the Jacobian matrix for a function f(y) with m components in n independent variables. 


Special
Functions 



Returns
the exponentially scaled complementary error function. 



Evaluates
the incomplete gamma function. 



Returns
the logarithmic derivative of the gamma function, also called the digamma
function. 



Returns
the ψ _{1} function, also known as the trigamma
function. 





Basic
Statistics 


Regression 



Returns
the intercept. 



Sets
the means of the variables. 




Analysis
of Variance 



Analyzes
a oneway classification model with covariates. 



Computes
the confidence interval associated with the difference of means between two
groups using a specified method. 


Time
Series and Forecasting 



Automatically
identifies time series outliers, determines parameters of a multiplicative
seasonal model and produces forecasts that incorporate the effects of
outliers whose effects persist beyond the end of the series. 



Detects
and determines outliers and simultaneously estimates the model parameters in
a time series whose underlying outlier free series follows a general seasonal
or nonseasonal ARMA model. Allows computation of
forecasts. 



Performs
lackoffit test for a univariate time series or transfer function given the
appropriate correlation function. 


Multivariate
Analysis 



Classifies
a set of observations using the linear or quadratic discriminant functions
generated during the training process. 



Removes
a set of observations from the discriminant functions. 



Returns
the number of rows of data encountered containing missing values ( 


Survival
and Reliability Analysis 



Computes
KaplanMeier (or productlimit) estimates of survival probabilities for a
sample of failure times that possibly contain right consoring.




Computes
the KaplanMeier reliability function estimates or the CDF based on failure
data that may be multicensored. 



Computes
population (current) or cohort life tables based upon the observed population
sizes at the middle (for population table) or the beginning (for cohort
table) of some user specified age intervals. 



Analyzes
survival and reliability data using Cox's proportional hazards model. 


Probability
Distribution Functions and Inverses 


Evaluates
the noncentral beta cumulative distribution
function (CDF). 


Evaluates
the noncentral F cumulative distribution function
(CDF). 


Evaluates
the logistic cumulative probability distribution function. 


Evaluates
the Pareto cumulative probability distribution function. 


Returns
the inverse of the logistic cumulative probability distribution function. 


Evaluates
the inverse of the noncentral beta cumulative
distribution function (CDF). 


Evaluates
the inverse of the noncentral F cumulative
distribution function (CDF). 


Returns
the inverse of the Pareto cumulative probability distribution function. 


Evaluates
the logistic probability density function. 


Evaluates
the noncentral beta probability density function
(PDF). 


Evaluates
the noncentral chisquared probability density
function. 


Evaluates
the noncentral F probability density function
(PDF). 


Evaluates
the noncentral Student's t probability density
function. 


Evaluates
the normal (Gaussian) probability density function. 


Evaluates
the Pareto probability density function. 


Public
interface for the usersupplied distribution function. 


Public
interface for the usersupplied probability distribution function. 


Evaluates
a gamma probability distribution. 


Evaluates
a lognormal probability distribution. 


Evaluates
a normal (Gaussian) probability distribution. 


Evaluates
a Poisson probability distribution. 

Random
Number Generation 


Generates
a canonical correlation matrix from an arbitrarily distributed multivariate
deviate sequence with a Gaussian Copula dependence structure. 


Generate
pseudorandom numbers from a Gaussian Copula distribution. 


Generate
pseudorandom numbers from a Student's t Copula distribution. 


Generates
pseudorandom numbers using the Ziggurat method. 



Finance 


Component
of DayCountBasis. The day count basis consists of a
month basis and a yearly basis. Each of these components implements this
interface. 


The
Day Count Basis. Rules for computing the number or days between two dates or
number of days in a year. 



Chart
2D 


Draws
an annotation. 


Draws
an image such that any portion of the image beyond the axis range is clipped. 


Treemap creates a chart from two arrays of double precision values
or one data array and one array of java.awt.Color
values. 



Data
Mining 


Trains
a Naive Bayes Classifier 
