Index

_

__call__() (scipy.stats.rv_continuous method)

__init__() (dora.active_sampling.active_sampling.Sampler method) (dora.active_sampling.ArrayBuffer method) (dora.active_sampling.Delaunay method) (dora.active_sampling.GaussianProcess method) (dora.active_sampling.Sampler method) (dora.active_sampling.delaunay_sampler.Delaunay method) (dora.active_sampling.gp_sampler.GaussianProcess method) (dora.active_sampling.util.ArrayBuffer method) (dora.regressors.gp.Folds method) (dora.regressors.gp.OptConfig method) (dora.regressors.gp.QueryParams method) (dora.regressors.gp.Range method) (dora.regressors.gp.RegressionParams method) (scipy.stats.gaussian_kde method) (scipy.stats.rv_continuous method) (scipy.stats.rv_discrete method)

A

acq_name (dora.active_sampling.GaussianProcess attribute) (dora.active_sampling.gp_sampler.GaussianProcess attribute) add_data() (in module dora.regressors.gp) alpha (in module scipy.stats) anderson() (in module scipy.stats) anderson_ksamp() (in module scipy.stats) anglit (in module scipy.stats)

ansari() (in module scipy.stats) app (in module dora.server) arcsine (in module scipy.stats) ArrayBuffer (class in dora.active_sampling) (class in dora.active_sampling.util) auto_range() (in module dora.regressors.gp)

B

bartlett() (in module scipy.stats) bayes_mvs() (in module scipy.stats) bernoulli (in module scipy.stats) beta (in module scipy.stats) betaprime (in module scipy.stats) binned_statistic() (in module scipy.stats) binned_statistic_2d() (in module scipy.stats) binned_statistic_dd() (in module scipy.stats) binom (in module scipy.stats)

binom_test() (in module scipy.stats) boltzmann (in module scipy.stats) boxcox() (in module scipy.stats) boxcox_llf() (in module scipy.stats) boxcox_normmax() (in module scipy.stats) boxcox_normplot() (in module scipy.stats) bradford (in module scipy.stats) burr (in module scipy.stats)

C

cauchy (in module scipy.stats) cdf() (in module scipy.stats), [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81], [82], [83], [84], [85], [86], [87], [88], [89], [90], [91], [92], [93], [94] (scipy.stats.rv_continuous method), [1] (scipy.stats.rv_discrete method) (scipy.stats.rv_discrete.generic method) chi (in module scipy.stats) chi2 (in module scipy.stats) chi2_contingency() (in module scipy.stats) chisquare() (in module scipy.stats)

compose() (in module dora.regressors.gp) condition() (in module dora.regressors.gp) cosine (in module scipy.stats) covariance (scipy.stats.gaussian_kde attribute) cumfreq() (in module scipy.stats)

D

d (scipy.stats.gaussian_kde attribute) dataset (scipy.stats.gaussian_kde attribute) Delaunay (class in dora.active_sampling) (class in dora.active_sampling.delaunay_sampler) describe() (in module scipy.stats) dgamma (in module scipy.stats) dims (dora.active_sampling.active_sampling.Sampler attribute) (dora.active_sampling.Sampler attribute) dlaplace (in module scipy.stats) dora.active_sampling.active_sampling (module)

dora.regressors.gp.kernel (module) dora.regressors.gp.linalg (module) dora.regressors.gp.predict (module) dora.regressors.gp.train (module) dora.regressors.gp.types (module) dora.server.response (module) dora.server.server (module) dweibull (in module scipy.stats)

E

entropy() (in module scipy.stats), [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81], [82], [83], [84], [85], [86], [87], [88], [89], [90], [91], [92], [93], [94], [95], [96] (scipy.stats.rv_continuous method), [1] (scipy.stats.rv_discrete method) (scipy.stats.rv_discrete.generic method) erlang (in module scipy.stats) expect() (in module scipy.stats), [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81], [82], [83], [84], [85], [86], [87], [88], [89], [90], [91], [92], [93], [94] (scipy.stats.rv_continuous method) (scipy.stats.rv_discrete method) expected_freq() (in module scipy.stats.contingency)

explore_priority (dora.active_sampling.Delaunay attribute) (dora.active_sampling.GaussianProcess attribute) (dora.active_sampling.delaunay_sampler.Delaunay attribute) (dora.active_sampling.gp_sampler.GaussianProcess attribute) expon (in module scipy.stats) exponpow (in module scipy.stats) exponweib (in module scipy.stats)

F

f (in module scipy.stats) f_oneway() (in module scipy.stats) factor (scipy.stats.gaussian_kde attribute) fatiguelife (in module scipy.stats) fisher_exact() (in module scipy.stats) fisk (in module scipy.stats) fit() (in module scipy.stats), [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81] (scipy.stats.rv_continuous method), [1]

fligner() (in module scipy.stats) foldcauchy (in module scipy.stats) foldnorm (in module scipy.stats) Folds (class in dora.regressors.gp) frechet_l (in module scipy.stats) frechet_r (in module scipy.stats) friedmanchisquare() (in module scipy.stats)

G

gamma (in module scipy.stats) gausshyper (in module scipy.stats) gaussian_kde (class in scipy.stats) GaussianProcess (class in dora.active_sampling) (class in dora.active_sampling.gp_sampler) generic() (scipy.stats.rv_discrete method) genexpon (in module scipy.stats) genextreme (in module scipy.stats) gengamma (in module scipy.stats) genhalflogistic (in module scipy.stats) genlogistic (in module scipy.stats)

genpareto (in module scipy.stats) geom (in module scipy.stats) get_query() (in module dora.server) gilbrat (in module scipy.stats) gmean() (in module scipy.stats) gompertz (in module scipy.stats) grid_sample() (in module dora.active_sampling) gumbel_l (in module scipy.stats) gumbel_r (in module scipy.stats)

H

halfcauchy (in module scipy.stats) halflogistic (in module scipy.stats) halfnorm (in module scipy.stats) histogram() (in module scipy.stats) histogram2() (in module scipy.stats)

hmean() (in module scipy.stats) hypergeom (in module scipy.stats) hyperparams (dora.active_sampling.GaussianProcess attribute) (dora.active_sampling.gp_sampler.GaussianProcess attribute) hypsecant (in module scipy.stats)

I

initialise_sampler() (in module dora.server) interval() (in module scipy.stats), [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81], [82], [83], [84], [85], [86], [87], [88], [89], [90], [91], [92], [93], [94] (scipy.stats.rv_continuous method) (scipy.stats.rv_discrete.generic method) inv_cov (scipy.stats.gaussian_kde attribute) invgamma (in module scipy.stats)

invgauss (in module scipy.stats) invweibull (in module scipy.stats) isf() (in module scipy.stats), [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81], [82], [83], [84], [85], [86], [87], [88], [89], [90], [91], [92], [93], [94] (scipy.stats.rv_continuous method), [1] (scipy.stats.rv_discrete method) (scipy.stats.rv_discrete.generic method) itemfreq() (in module scipy.stats)

J

johnsonsb (in module scipy.stats)

johnsonsu (in module scipy.stats)

K

kendalltau() (in module scipy.stats) kerneldef (dora.active_sampling.GaussianProcess attribute) (dora.active_sampling.gp_sampler.GaussianProcess attribute) kruskal() (in module scipy.stats) ks_2samp() (in module scipy.stats) ksone (in module scipy.stats)

kstest() (in module scipy.stats) kstwobign (in module scipy.stats) kurtosis() (in module scipy.stats) kurtosistest() (in module scipy.stats)

L

laplace (in module scipy.stats) learn() (in module dora.regressors.gp) levene() (in module scipy.stats) linregress() (in module scipy.stats) logcdf() (in module scipy.stats), [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81], [82], [83], [84], [85], [86], [87], [88], [89], [90], [91], [92], [93], [94] (scipy.stats.rv_continuous method), [1] (scipy.stats.rv_discrete method) (scipy.stats.rv_discrete.generic method) loggamma (in module scipy.stats) logistic (in module scipy.stats) loglaplace (in module scipy.stats)

lognorm (in module scipy.stats) logpdf() (in module scipy.stats), [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81], [82] (scipy.stats.rv_continuous method), [1] logpmf() (in module scipy.stats), [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12] (scipy.stats.rv_discrete method), [1] logser (in module scipy.stats) logsf() (in module scipy.stats), [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81], [82], [83], [84], [85], [86], [87], [88], [89], [90], [91], [92], [93], [94] (scipy.stats.rv_continuous method), [1] (scipy.stats.rv_discrete method) (scipy.stats.rv_discrete.generic method) lomax (in module scipy.stats) lower (dora.active_sampling.active_sampling.Sampler attribute) (dora.active_sampling.Sampler attribute)

M

mannwhitneyu() (in module scipy.stats) margins() (in module scipy.stats.contingency) maxwell (in module scipy.stats) mean() (in module dora.regressors.gp) (in module scipy.stats), [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81], [82], [83], [84], [85], [86], [87], [88], [89], [90], [91], [92], [93], [94] (scipy.stats.rv_continuous method) (scipy.stats.rv_discrete.generic method) median() (in module scipy.stats), [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81], [82], [83], [84], [85], [86], [87], [88], [89], [90], [91], [92], [93], [94] (scipy.stats.rv_continuous method) (scipy.stats.rv_discrete.generic method)

mielke (in module scipy.stats) mode() (in module scipy.stats) moment() (in module scipy.stats), [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81], [82] (scipy.stats.rv_continuous method), [1] (scipy.stats.rv_discrete method) (scipy.stats.rv_discrete.generic method) mood() (in module scipy.stats) multivariate_normal (in module scipy.stats)

N

n (scipy.stats.gaussian_kde attribute) n_min (dora.active_sampling.GaussianProcess attribute) (dora.active_sampling.gp_sampler.GaussianProcess attribute) n_tasks (dora.active_sampling.GaussianProcess attribute) (dora.active_sampling.gp_sampler.GaussianProcess attribute) nakagami (in module scipy.stats) nanmean() (in module scipy.stats) nanmedian() (in module scipy.stats) nanstd() (in module scipy.stats)

nbinom (in module scipy.stats) ncf (in module scipy.stats) nct (in module scipy.stats) ncx2 (in module scipy.stats) norm (in module scipy.stats) normaltest() (in module scipy.stats)

O

obrientransform() (in module scipy.stats)

OptConfig (class in dora.regressors.gp)

P

pareto (in module scipy.stats) pdf() (in module scipy.stats), [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81], [82] (scipy.stats.rv_continuous method), [1] pearson3 (in module scipy.stats) pearsonr() (in module scipy.stats) pending_results (dora.active_sampling.active_sampling.Sampler attribute) (dora.active_sampling.Sampler attribute) percentileofscore() (in module scipy.stats) planck (in module scipy.stats) pmf() (in module scipy.stats), [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12] (scipy.stats.rv_discrete method) (scipy.stats.rv_discrete.generic method) pointbiserialr() (in module scipy.stats) poisson (in module scipy.stats)

power_divergence() (in module scipy.stats) powerlaw (in module scipy.stats) powerlognorm (in module scipy.stats) powernorm (in module scipy.stats) ppcc_max() (in module scipy.stats) ppcc_plot() (in module scipy.stats) ppf() (in module scipy.stats), [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81], [82], [83], [84], [85], [86], [87], [88], [89], [90], [91], [92], [93], [94] (scipy.stats.rv_continuous method), [1] (scipy.stats.rv_discrete method) (scipy.stats.rv_discrete.generic method) predict() (in module dora.server) probplot() (in module scipy.stats)

Q

query() (in module dora.regressors.gp)

QueryParams (class in dora.regressors.gp)

R

randint (in module scipy.stats) random_sample() (in module dora.active_sampling) Range (class in dora.regressors.gp) rankdata() (in module scipy.stats) ranksums() (in module scipy.stats) rayleigh (in module scipy.stats) rdist (in module scipy.stats) recipinvgauss (in module scipy.stats) reciprocal (in module scipy.stats) RegressionParams (class in dora.regressors.gp)

regressors (dora.active_sampling.GaussianProcess attribute) (dora.active_sampling.gp_sampler.GaussianProcess attribute) relfreq() (in module scipy.stats) retrieve_settings() (in module dora.server) retrieve_trainingdata() (in module dora.server) returns_json() (in module dora.server) rice (in module scipy.stats) rv_continuous (class in scipy.stats) rv_discrete (class in scipy.stats) rvs() (in module scipy.stats), [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81], [82], [83], [84], [85], [86], [87], [88], [89], [90], [91], [92], [93], [94], [95] (scipy.stats.rv_continuous method) (scipy.stats.rv_discrete method) (scipy.stats.rv_discrete.generic method)

S

Sampler (class in dora.active_sampling) (class in dora.active_sampling.active_sampling) scoreatpercentile() (in module scipy.stats) sem() (in module scipy.stats) semicircular (in module scipy.stats) sf() (in module scipy.stats), [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81], [82], [83], [84], [85], [86], [87], [88], [89], [90], [91], [92], [93], [94] (scipy.stats.rv_continuous method), [1] (scipy.stats.rv_discrete method) (scipy.stats.rv_discrete.generic method) shapiro() (in module scipy.stats) sigmaclip() (in module scipy.stats) signaltonoise() (in module scipy.stats)

simplex_cache (dora.active_sampling.Delaunay attribute) (dora.active_sampling.delaunay_sampler.Delaunay attribute) skellam (in module scipy.stats) skew() (in module scipy.stats) skewtest() (in module scipy.stats) spearmanr() (in module scipy.stats) StackedGP (in module dora.server) stats() (in module scipy.stats), [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81], [82], [83], [84], [85], [86], [87], [88], [89], [90], [91], [92], [93], [94] (scipy.stats.rv_continuous method), [1] (scipy.stats.rv_discrete method) (scipy.stats.rv_discrete.generic method) std() (in module scipy.stats), [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81], [82], [83], [84], [85], [86], [87], [88], [89], [90], [91], [92], [93], [94] (scipy.stats.rv_continuous method) (scipy.stats.rv_discrete.generic method)

T

t (in module scipy.stats) threshold() (in module scipy.stats) tiecorrect() (in module scipy.stats) tmax() (in module scipy.stats) tmean() (in module scipy.stats) tmin() (in module scipy.stats) triang (in module scipy.stats) triangulation (dora.active_sampling.Delaunay attribute) (dora.active_sampling.delaunay_sampler.Delaunay attribute) trim1() (in module scipy.stats) trimboth() (in module scipy.stats)

truncexpon (in module scipy.stats) truncnorm (in module scipy.stats) tsem() (in module scipy.stats) tstd() (in module scipy.stats) ttest_1samp() (in module scipy.stats) ttest_ind() (in module scipy.stats) ttest_rel() (in module scipy.stats) tukeylambda (in module scipy.stats) tvar() (in module scipy.stats)

U

uniform (in module scipy.stats) update_sampler() (in module dora.server)

upper (dora.active_sampling.active_sampling.Sampler attribute) (dora.active_sampling.Sampler attribute)

V

var() (in module scipy.stats), [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81], [82], [83], [84], [85], [86], [87], [88], [89], [90], [91], [92], [93], [94] (scipy.stats.rv_continuous method) (scipy.stats.rv_discrete.generic method) variance() (in module dora.regressors.gp) variation() (in module scipy.stats)

virtual_flag (dora.active_sampling.active_sampling.Sampler attribute) (dora.active_sampling.Sampler attribute) vonmises (in module scipy.stats)

W

wald (in module scipy.stats) weibull_max (in module scipy.stats) weibull_min (in module scipy.stats)

wilcoxon() (in module scipy.stats) wrapcauchy (in module scipy.stats)

X

X (dora.active_sampling.active_sampling.Sampler attribute) (dora.active_sampling.Sampler attribute)

Y

y (dora.active_sampling.active_sampling.Sampler attribute) (dora.active_sampling.Sampler attribute)

y_mean (dora.active_sampling.GaussianProcess attribute) (dora.active_sampling.gp_sampler.GaussianProcess attribute)

Z

zipf (in module scipy.stats) zmap() (in module scipy.stats)

zscore() (in module scipy.stats)