Constants

const double stat_tool::COMPOUND_THRESHOLD = 0.99999

threshold on the cumulative distribution function for determining the upper bound of the support in compound distributions

const double stat_tool::COMPOUND_INIT_PROBABILITY = 0.001

threshold for probability initialization in compound distributions

const double stat_tool::COMPOUND_LIKELIHOOD_DIFF = 1.e-5

threshold for stopping EM iterations in compound distributions

const int stat_tool::COMPOUND_NB_ITER = 10000

maximum number of EM iterations in compound distributions

const double stat_tool::COMPOUND_DIFFERENCE_WEIGHT = 0.5

default penalty weight (1st- or 2nd-order difference cases) in compound distributions

const double stat_tool::COMPOUND_ENTROPY_WEIGHT = 0.1

default penalty weight (entropy case) in compound distributions

const int stat_tool::COMPOUND_COEFF = 10

rounding coefficient for the estimator in compound distributions

static const double stat_tool::bilateral_tail[7] = {0.05, 0.025, 0.01, 0.005, 0.0025, 0.001, 0.0005}

default quantiles in continuous parametric processes

static const double stat_tool::posterior_threshold[7] = {0.25, 0.1, 0.05, 0.025, 0.01, 0.005, 0.0025}

default probability thresholds in continuous parametric processes

const int stat_tool::CONVOLUTION_NB_DISTRIBUTION = 10

maximum number of elementary distributions in convoluations

const double stat_tool::CONVOLUTION_THRESHOLD = 0.9999

threshold on the cumulative distribution function for determining the upper bound of the support in convolutions

const double stat_tool::CONVOLUTION_INIT_PROBABILITY = 0.001

threshold for probability initialization in convolutions

const double stat_tool::CONVOLUTION_LIKELIHOOD_DIFF = 1.e-5

threshold for stopping EM iterations in convolutions

const int stat_tool::CONVOLUTION_NB_ITER = 10000

maximum number of EM iterations in convolutions

const double stat_tool::CONVOLUTION_DIFFERENCE_WEIGHT = 0.5

default penalty weight (1st- or 2nd-order difference cases) in convolutions

const double stat_tool::CONVOLUTION_ENTROPY_WEIGHT = 0.1

default penalty weight (entropy case) in convolutions

const int stat_tool::CONVOLUTION_COEFF = 10

rounding coefficient for the estimator in convolutions

const int stat_tool::MAX_FREQUENCY = 50

maximum frequency for smoothing curves

const int stat_tool::MAX_RANGE = 2

maximum half-width of the smoothing window

const int stat_tool::PLOT_NB_CURVE = 12

maximum number of curves (Gnuplot output)

const int stat_tool::PLOT_MIN_FREQUENCY = 10

minimum frequency for plotting curve points (Gnuplot output)

const int stat_tool::DISCRETE_MIXTURE_NB_COMPONENT = 100

maximum number of components for discrete mixtures

const double stat_tool::NEGATIVE_BINOMIAL_PARAMETER = 20.

initial parameter for a negative binomial distribution

const double stat_tool::MIN_WEIGHT_STEP = 0.1

minimum step for weight initialization in discrete mixtures

const double stat_tool::MAX_WEIGHT_STEP = 0.5

maximum step for weight initialization in discrete mixtures

const int stat_tool::DISCRETE_MIXTURE_COEFF = 2

rounding coefficient for the estimator in discrete mixtures

const double stat_tool::DISCRETE_MIXTURE_LIKELIHOOD_DIFF = 1.e-5

threshold for stopping the EM iterations in discrete mixtures

const int stat_tool::DISCRETE_MIXTURE_NB_ITER = 500

maximum number of EM iterations in discrete mixtures

const int stat_tool::ASCII_NB_INDIVIDUAL = 10

maximum number of individuals for displaying the results of individual alignments

const double stat_tool::PLOT_YMARGIN = 0.1

y axis margin for the plotting of distances

const double stat_tool::DISTANCE_ROUNDNESS = 1.e-12

distance rounding value

const int stat_tool::GLOBAL_NB_ITER = 20

number of iterations when the clusters are globally computed in hierarchical clustering

const int stat_tool::PARTITIONING_NB_ITER_1 = 50

maximum number of iterations in clustering: partitioning variant 1

const int stat_tool::PARTITIONING_NB_ITER_2 = 20

maximum number of iterations in clustering: partitioning variant 2

const int stat_tool::NB_STATE = 100

maximum number of states of a Markov chain

const int stat_tool::ORDER = 8

maximum order of a Markov chain

const double stat_tool::MIN_PROBABILITY = 1.e-5

minimum initial/transition/categorical observation probability

const double stat_tool::THRESHOLDING_FACTOR = 0.8

const int stat_tool::NB_PARAMETER = 100000

maximum number of parameters of a Markov chain

const int stat_tool::NB_OUTPUT_PROCESS = 15

maximum number of observation processes

const int stat_tool::NB_OUTPUT = 25

maximum number of observed categories per state (categorical case)

const double stat_tool::OBSERVATION_THRESHOLD = 0.999

threshold on the cumulative distribution function for bounding a discrete parametric observation distribution

const double stat_tool::ACCESSIBILITY_THRESHOLD = 1.e-6

threshold for stopping the probabilistic algorithm for computing state accessibility

const int stat_tool::ACCESSIBILITY_LENGTH = 100

maximum sequence length for the probabilistic algorithm

for computing state accessibility

const double stat_tool::NOISE_PROBABILITY = 0.05

perturbation of observation probabilities

const double stat_tool::MEAN_SHIFT_COEFF = 0.1

coefficient for shifting continuous observation distributions

const int stat_tool::MIN_NB_ELEMENT = 10

minimum size of the sample built by rounding

const int stat_tool::OBSERVATION_COEFF = 10

rounding coefficient for the parametric observation distribution estimator

const int stat_tool::GAMMA_MAX_NB_DECIMAL = 6

maximum number of decimals for the simulation of a gamma distribution

const int stat_tool::INVERSE_GAUSSIAN_MAX_NB_DECIMAL = 6

maximum number of decimals for the simulation

of an inverse Gaussian distribution

const int stat_tool::GAUSSIAN_MAX_NB_DECIMAL = 6

maximum number of decimals for the simulation of a Gaussian distribution

const int stat_tool::DEGREE_DECIMAL_SCALE = 10

factor for determining the number of decimals for the simulation of a von Mises distribution in degrees

const int stat_tool::RADIAN_DECIMAL_SCALE = 1000

factor for determining the number of decimals for the simulation of a von Mises distribution in radians

const double stat_tool::MVMIXTURE_LIKELIHOOD_DIFF = 1.e-8

const int stat_tool::MIXTURE_COEFF = 2

const double stat_tool::CUMUL_THRESHOLD = 0.999

const double stat_tool::BISECTION_RATIO_THRESHOLD = 1.e-8

const int stat_tool::BISECTION_NB_ITER = 100

const int stat_tool::REGRESSION_NB_VECTOR = 10000

const int stat_tool::NEIGHBORHOOD = 3

const int stat_tool::ERROR_LENGTH = 200

const int stat_tool::I_DEFAULT = -1

default value for int

const double stat_tool::D_DEFAULT = -1.

default value for double

const double stat_tool::D_INF = -1.e37

smallest real number

const double stat_tool::DOUBLE_ERROR = 1.e-6

error on a sum of doubles

const int stat_tool::NB_CRITICAL_PROBABILITY = 2

default bound on a number of mutliple tests

const double stat_tool::ref_critical_probability[NB_CRITICAL_PROBABILITY] = {0.05, 0.01}

default levels of tests

const int stat_tool::NB_VALUE = 1000

number of values of a discrete variable

const int stat_tool::SAMPLE_NB_VALUE = NB_VALUE

number of values of a discrete sample

const int stat_tool::MAX_INF_BOUND = 10000

maximum lower bound

const int stat_tool::MAX_DIFF_BOUND = 10000

maximum difference between lower and upper bounds

const double stat_tool::MAX_MEAN = 10000.

maximum mean

const int stat_tool::MAX_SEQUENCE_LENGTH = 10000

maximum sequence length for computing prior segment length distributions

const double stat_tool::B_PROBABILITY = 0.8

threshold for using the backward computation of the binomial probability mass function

const double stat_tool::B_THRESHOLD = 1000.

const double stat_tool::P_THRESHOLD = 90.

threshold for using the computation in log of the Poisson probability mass function

const double stat_tool::NB_THRESHOLD = 500.

threshold for using the computation in log of the negative binomial probability mass function

const double stat_tool::SAMPLE_NB_VALUE_COEFF = 5.

factor for deducing the number of possible values of a distribution from the number of possible values of a frequency distribution

const int stat_tool::INF_BOUND_MARGIN = 5

range of values for the lower bound

const int stat_tool::SUP_BOUND_MARGIN = 3

range of values for the upper bound

const double stat_tool::POISSON_RATIO = 0.7

minimum mean/variance ratio for estimating a Poisson distribution

const double stat_tool::POISSON_RANGE = 0.1

range for selecting a Poisson distribution by time scaling of another discrete distribution

const double stat_tool::NB_VALUE_COEFF = 2.

factor for deducing the number of values of a distribution from the number of values of an initial distribution

const int stat_tool::MIN_RANGE = 10

minimum interval of values for applying the rejection sampling method

const double stat_tool::MAX_SURFACE = 3.

maximum surface for applying the rejection sampling method

const int stat_tool::DIST_NB_ELEMENT = 1000000

maximum sample size for simulation

const int stat_tool::NB_COMPLETE_INTERVAL = 3

minimum number of complete time intervals

const double stat_tool::RENEWAL_LIKELIHOOD_DIFF = 1.e-5

threshold for stopping the EM iterations

const int stat_tool::RENEWAL_NB_ITER = 10000

maximum number of EM iterations

const double stat_tool::RENEWAL_DIFFERENCE_WEIGHT = 0.5

default penalty weight (1st- or 2nd-order difference cases)

const double stat_tool::RENEWAL_ENTROPY_WEIGHT = 0.05

default penalty weight (entropy case)

const double stat_tool::MAX_VALUE_COEFF = 10.

coefficient for deducing the maximum value of an inter-event distribution

const double stat_tool::CONTINUOUS_POSITIVE_INF_BOUND = 1.e-12

inf bound of positive continuous distribution support (bug boost C++)

const double stat_tool::GAMMA_TAIL = 1.e-3

gamma distribution tail

const int stat_tool::GAMMA_NB_STEP = 1000

number of steps for computing a discretized gamma distribution

const int stat_tool::GAMMA_NB_SUB_STEP = 10

number of sub-steps for computing a discretized gamma distribution

const double stat_tool::GAMMA_INVERSE_SAMPLE_SIZE_FACTOR = 5.

factor for the gamma distribution corrected moment estimator

const double stat_tool::GAMMA_MIN_SHAPE_PARAMETER = 0.1

minimum shape parameter (gamma distribution)

const double stat_tool::GAMMA_DEFAULT_SCALE_PARAMETER = 1

default scale parameter (gamma distribution)

const double stat_tool::GAMMA_ZERO_FREQUENCY_THRESHOLD = 0.999

threshold on the zero relative frequency (gamma distribution estimation)

const double stat_tool::GAMMA_SHAPE_PARAMETER_THRESHOLD = 3.

threshold on the shape parameter (gamma distribution estimation)

const double stat_tool::GAMMA_FREQUENCY_THRESHOLD = 100.

threshold on the frequency (gamma distribution estimation)

const double stat_tool::GAMMA_ITERATION_FACTOR = 0.5

factor (gamma distribution estimation)

const int stat_tool::GAMMA_MAX_NB_ITERATION = 5

maximum number of iterations (gamma distribution estimation)

const double stat_tool::INVERSE_GAUSSIAN_TAIL = 1.e-3

inverse Gaussian distribution tail

const int stat_tool::INVERSE_GAUSSIAN_NB_STEP = 1000

number of steps for computing a discretized inverse Gaussian distribution

const int stat_tool::INVERSE_GAUSSIAN_NB_SUB_STEP = 10

number of steps for computing a discretized inverse Gaussian distribution

const double stat_tool::GAUSSIAN_TAIL = 5.e-4

Gaussian distribution tail.

const int stat_tool::GAUSSIAN_NB_STEP = 1000

number of steps for computing a discretized Gaussian distribution

const int stat_tool::GAUSSIAN_NB_SUB_STEP = 10

number of steps for computing a discretized Gaussian distribution

const double stat_tool::GAUSSIAN_MIN_VARIATION_COEFF = 1.e-3

minimum coefficient of variation (Gaussian distribution estimation)

const int stat_tool::VON_MISES_NB_STEP = 3600

number of steps for computing a discretized von Mises distribution

const int stat_tool::VON_MISES_NB_SUB_STEP = 10

number of steps for computing a discretized von Mises distribution

const int stat_tool::CHI2_FREQUENCY = 2

minimum theoretical sample size for a Chi2 goodness of fit test

const int stat_tool::MARGINAL_DISTRIBUTION_MAX_VALUE = 25000

maximum value for the building of a marginal frequency distribution

const int stat_tool::HISTOGRAM_FREQUENCY = 10

average frequency for defining the bin width of an histogram

const double stat_tool::SKEWNESS_ROUNDNESS = 1.e-2

rounding on the coefficient of skewness

const int stat_tool::NB_ERROR = 10

maximum number of recorded errors

const int stat_tool::LINE_NB_CHARACTER = 100

number of characters per line for sequences

const int stat_tool::ASCII_NB_VALUE = 15

maximum number of values (ASCII display)

const int stat_tool::ASCII_SPACE = 2

number of empty spaces between 2 columns (ASCII display)

const double stat_tool::ASCII_ROUNDNESS = 1.e-5

rounding on the cumulative distribution function for bounding a distribution (ASCII display)

const double stat_tool::SPREADSHEET_ROUNDNESS = 1.e-7

rounding on the cumulative distribution function for bounding a distribution (spreadsheet output)

const int stat_tool::DISPLAY_NB_INDIVIDUAL = 50

maximum number of displayed individuals

const int stat_tool::PLOT_NB_DISTRIBUTION = 15

maximum number of plotted distributions

const int stat_tool::PLOT_NB_HISTOGRAM = 15

maximum number of plotted histograms

const double stat_tool::PLOT_ROUNDNESS = 1.e-5

rounding on the cumulative distribution function for bounding a plotted distribution

const double stat_tool::PLOT_SHIFT = 0.2

shift between 2 plotted frequency distributions

const double stat_tool::PLOT_MAX_SHIFT = 0.5

maximum shift between the first and last plotted frequency distributions

const int stat_tool::TIC_THRESHOLD = 10

minimum number of plotted graduations

const double stat_tool::PLOT_MASS_THRESHOLD = 1.e-3

minimum value for plotting a zero mass after the last possible value

const double stat_tool::YSCALE = 1.1

scale factor for y axis in plots

const double stat_tool::PLOT_RANGE_RATIO = 4.

threshold for plotting from 0

static const double stat_tool::CRITICAL_PROBABILITY_FACTOR = 1.2

const int stat_tool::VECTOR_NB_VARIABLE = 60

maximum number of variables

const int stat_tool::DISTANCE_NB_VECTOR = 2000

maximum number of vectors for the computation of a matrix of pairwise distances

const int stat_tool::SUP_NORM_DISTANCE_NB_VECTOR = 10

minimum number of vectors for the computation of the sup norm distance

const int stat_tool::CONTINGENCY_NB_VALUE = 100

maximum number of categories for the computation of a contingency table

const int stat_tool::DISPLAY_CONTINGENCY_NB_VALUE = 20

maximum number of categories for the display of a contingency table

const int stat_tool::VARIANCE_ANALYSIS_NB_VALUE = 100

maximum number of levels for the analysis of variance

const int stat_tool::DISPLAY_CONDITIONAL_NB_VALUE = 100

maximum number of values of the display of the conditional distributions

const int stat_tool::PLOT_NB_VALUE = 30

threshold for the writing of frequencies (Gnuplot output)

const int stat_tool::NB_CATEGORY = 50

maximum number of categories

const int stat_tool::MIN_NB_ASSIGNMENT = 1

minimum number of assignments of individuals (1st iteration of the MCEM algorithm)

const int stat_tool::MAX_NB_ASSIGNMENT = 10

maximum number of assignments of individuals (MCEM algorithm)

const double stat_tool::NB_ASSIGNMENT_PARAMETER = 1.

parameter for the number of assignments of individuals (MCEM algorithm)