|
| |
- as6.f90
Cholesky factorization of symmetric positive definite matrix with only lower
triangle stored as a vector (2 versions).
- as7.f90
Inversion of symmetric positive definite matrix with only lower triangle
stored as a vector using AS6 (2 versions). Includes short test program and
interfaces.
- as27.f90
Upper tail area under Student's t-distribution.
- as60.f90
Calculates the eigenvalues/vectors of a real symmetric matrix.
- as63.f90
Computes the incomplete beta function. The file includes a module for the
log of the beta function, which also has the log of the gamma function.
- as66.f90
Area under the normal curve.
- as91.f90
Returns percentage points of the chi-squared distribution for input tail
probabilities and numbers of degrees of freedom.
- as110
Lp-norm fitting of straight lines, particularly for 1 <= p <= 2, by extension
of an algorithm of Schlossmacher.
- chirp.f90
The CHIRP-Z Fast Fourier transform for series of arbitrary length. Refer to
the journal article for instructions on its use. Includes FFT for the usual
case when series length is a power of 2. this is AS120.
- as126
Calculates the distribution function for the range for a sample of size n
from the standard normal distribution.
- as132.f90
Minimize the sum of absolute deviations for a simple Y on X linear regression.
- as135.f90
Min-Max (L-infinity) estimates for linear multiple regression, includes
a test program.
- as136.f90
A K-means clustering algorithm.
- as152.f90
Cumulative hypergeometric probabilities.
- as154.f90
Combines AS 154 & 182, for the exact maximum likelihood estimation of
parameters of ARIMA models using Kalman filtering.
- as155.f90
Distribution of a linear combination of non-central chi-squared random
variables. This code is NOT compatible with Lahey's ELF90 compiler.
- as157.f90
The runs-up and runs-down tests.
- as177.f90
Calculates the expected values of normal order statistics.
- as181.f90
Calculates the Shapiro-Wilks statistic and its P-value. Actually uses ASR94.
- as190.f90
Distribution function and its inverse, for the studentized range.
- as192.f90
Computes approximate significance points of a Pearson curve with given
first four moments, or first three moments and left or right boundary.
- as205.f90
Enumeration of all R x C contingency tables with given row and column totals,
and calculation of hypergeometric probability for each table.
- as207.f90
Fits a general log-linear model. N.B. The F90 version has NOT been tested by
me (Alan Miller).
- as217.f90
Does the dip calculation for an ordered vector X using the greatest convex
minorant and the least concave majorant, skipping through the data using the
change points of these distributions.
It returns the dip statistic 'DIP' and the modal interval (XL, XU).
- as227.f90
Generates all possible N-bit binary codes.
- as239.f90
Integral of the gamma distribution
- as241.f90
Calculate the normal deviate (z-score) corresponding to a given area under the
normal curve
- as245.f90
Log of the gamma function
- as260.f90
Calculates the distribution function of the square (R^2) of the multiple
correlation coefficient.
- as261.f90
Quantiles of the distribution of R^2.
- as275.f90
Calculation of the non-central chi-squared distribution function.
- as282.f90
Robust regression using the least median of squares (LMS) criterion.
There is also a test program: t_as282.f90
- as285.f90
Multivariate normal probabilities over regions defined in a user-supplied function.
- as286.zip
Parameter estimation for non-linear errors-in-variables problems. I have added
a third example, fitting a cylinder, to the two which were in the published
version. This is a ZIP file.
- as290.f90
Generates a rectangular grid which can be used for contour plotting of
confidence limits in nonlinear regression. Also outputs the F-values for
the confidence levels selected. The test program: t_as290.f90
produces the grid for the beanroot data used in the paper in
Applied Statistics: beanroot.dat
- as295.f90
Algorithm for generating designs of experiments which are close to D-optimal.
The user supplies the set of NCAND candidate design points and the algorithm
picks a subset of N of them. Tha main uses of this algorithm are likely to be
for choosing designs in situations in which there are blocks of an awkward
size, and for augmenting an experiment which has already been carried out. Two
driver programs are provided here: fr_fac23.f90
for 2^p x 3^q fractional factorial experiments with possibly unequal block
sizes, and ibquad.f90
for quadratic surface designs with possibly unequal block sizes.
- as298.f90
Hybrid minimization routine using simulated annealing and a user-supplied
local minimizer. You should also look at Dr. Tibor Csendes' global
optimization package here.
- as304.f90
Fisher's non-parametric randomization test for two small independent random
samples.
- as310.f90
Incomplete beta function.
- as319.f90
Variable metric unconstrained function minimization without derivatives.
|
