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| double | vg::median (std::vector< int > &v) |
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| void | vg::wellford_update (size_t &count, double &mean, double &M2, double new_val) |
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| pair< double, double > | vg::wellford_mean_var (size_t count, double mean, double M2, bool sample_variance) |
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| template<typename T > |
| double | vg::stdev (const T &v) |
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| template<typename Number > |
| SummaryStatistics | vg::summary_statistics (const std::map< Number, size_t > &values) |
| | Returns summary statistics for a multiset of numbers. More...
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| double | vg::Phi (double x) |
| | The standard normal cumulative distribution function. More...
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| double | vg::Phi_inv (double quantile) |
| | Inverse CDF of a standard normal distribution. Must have 0 < quantile < 1. More...
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| double | vg::lognormal_pdf (double x, double mu, double sigma) |
| | Probability density function or log-normal distribution. More...
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| double | vg::add_log (double log_x, double log_y) |
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| double | vg::subtract_log (double log_x, double log_y) |
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| double | vg::ln_to_log10 (double ln) |
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| double | vg::log10_to_ln (double l10) |
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| double | vg::log10_add_one (double x) |
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| double | vg::add_log10 (double i, double j) |
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| double | vg::phred_for_at_least_one (size_t p, size_t n) |
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| double | vg::prob_for_at_least_one (size_t p, size_t n) |
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| template<typename T > |
| T | vg::normal_pdf (T x, T m=0.0, T s=1.0) |
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| double | vg::prob_to_logprob (double prob) |
| | Convert a probability to a natural log probability. More...
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| double | vg::logprob_to_prob (double logprob) |
| | Convert natural log probability to a probability. More...
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| double | vg::logprob_add (double logprob1, double logprob2) |
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| double | vg::logprob_invert (double logprob) |
| | Invert a logprob, and get the probability of its opposite. More...
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| double | vg::phred_to_prob (uint8_t phred) |
| | Convert 8-bit Phred quality score to probability of wrongness, using a lookup table. More...
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| double | vg::phred_to_prob (double phred) |
| | Convert floating point Phred quality score to probability of wrongness. More...
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| double | vg::prob_to_phred (double prob) |
| | Convert probability of wrongness to integer Phred quality score. More...
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| double | vg::phred_to_logprob (int phred) |
| | Convert a Phred quality score directly to a natural log probability of wrongness. More...
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| double | vg::logprob_to_phred (double logprob) |
| | Convert a natural log probability of wrongness directly to a Phred quality score. More...
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| double | vg::logprob_geometric_mean (double lnprob1, double lnprob2) |
| | Take the geometric mean of two logprobs. More...
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| double | vg::phred_geometric_mean (double phred1, double phred2) |
| | Take the geometric mean of two phred-encoded probabilities. More...
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| double | vg::phred_add (double phred1, double phred2) |
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| template<typename Collection > |
| Collection::value_type | vg::logprob_sum (const Collection &collection) |
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| template<typename Iterator > |
| std::iterator_traits< Iterator >::value_type | vg::phred_sum (const Iterator &begin_it, const Iterator &end_it) |
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| template<typename Collection > |
| Collection::value_type | vg::phred_sum (const Collection &collection) |
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| double | vg::slope (const std::vector< double > &x, const std::vector< double > &y) |
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| double | vg::fit_zipf (const vector< double > &y) |
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| double | vg::fit_fixed_shape_max_exponential (const vector< double > &x, double shape, double tolerance=1e-8) |
| | Returns the MLE rate parameter for the distribution of (shape) iid exponential RVs. More...
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| double | vg::fit_fixed_rate_max_exponential (const vector< double > &x, double rate, double tolerance=1e-8) |
| | Returns the MLE estimate for the number of iid exponential RVs the data are maxima of. More...
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| pair< double, double > | vg::fit_max_exponential (const vector< double > &x, double tolerance=1e-8) |
| | Returns the MLE rate and shape parameters of a max exponential. More...
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| double | vg::max_exponential_cdf (double x, double rate, double shape, double location=0.0) |
| | Return the CDF of a max exponential with the given parameters. More...
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| double | vg::max_exponential_log_likelihood (const vector< double > &x, double rate, double shape, double location=0.0) |
| | The log likelihood of a max exponential with the given parameters on the given data. More...
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| pair< double, double > | vg::fit_weibull (const vector< double > &x) |
| | Returns an estimate of the rate and shape parameters of a Weibull distribution. More...
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| tuple< double, double, double > | vg::fit_offset_weibull (const vector< double > &x, double tolerance=1e-8) |
| | Returns an estimate of the rate, shape, and location (minimum value) of a 3-parameter Weibull distribution. More...
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| double | vg::weibull_cdf (double x, double scale, double shape, double location=0.0) |
| | Return the CDF of a max exponential with the given parameters. More...
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| double | vg::weibull_log_likelihood (const vector< double > &x, double scale, double shape, double location=0.0) |
| | Returns the log likelihood of some data generated by a Weibull distribution. More...
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| double | vg::golden_section_search (const function< double(double)> &f, double x_min, double x_max, double tolerance=1e-8) |
| | Returns a local maximum of a function within an interval. More...
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| vector< vector< double > > | vg::transpose (const vector< vector< double >> &A) |
| | A shitty set of linear algebra functions. More...
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| vector< vector< double > > | vg::matrix_multiply (const vector< vector< double >> &A, const vector< vector< double >> &B) |
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| vector< double > | vg::matrix_multiply (const vector< vector< double >> &A, const vector< double > &b) |
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| vector< vector< double > > | vg::matrix_invert (const vector< vector< double >> &A) |
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| vector< double > | vg::regress (const vector< vector< double >> &X, vector< double > &y) |
| | Returns the coefficients of a regression (does not automatically compute constant) More...
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| real_t | vg::gamma_ln (real_t x) |
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| real_t | vg::factorial_ln (int n) |
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| real_t | vg::pow_ln (real_t m, int n) |
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| real_t | vg::choose_ln (int n, int k) |
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| real_t | vg::multinomial_choose_ln (int n, vector< int > k) |
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| real_t | vg::poisson_prob_ln (int observed, real_t expected) |
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| template<typename ProbIn > |
| real_t | vg::multinomial_sampling_prob_ln (const vector< ProbIn > &probs, const vector< int > &obs) |
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| template<typename ProbIn > |
| real_t | vg::binomial_cmf_ln (ProbIn success_logprob, size_t trials, size_t successes) |
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| template<typename ProbIn > |
| real_t | vg::geometric_sampling_prob_ln (ProbIn success_logprob, size_t trials) |
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| template<typename Iter > |
| bool | vg::advance_split (Iter start, Iter end) |
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| template<typename ProbIn > |
| real_t | vg::multinomial_censored_sampling_prob_ln (const vector< ProbIn > &probs, const unordered_map< vector< bool >, int > &obs) |
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| real_t | vg::ewens_af_prob_ln (const vector< int > &a, real_t theta) |
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Defines a range of statistical functions
