| /dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/tsa/arima/estimators/tests/ |
| H A D | test_hannan_rissanen.py | 28 initial_ar_order=22, unbiased=False)
51 initial_ar_order=22, unbiased=False)
108 hannan_rissanen(endog, ar_order=1, ma_order=1, unbiased=True)
116 endog, ar_order=1, ma_order=1, unbiased=None
121 endog, ar_order=1, ma_order=1, unbiased=True
131 endog, ar_order=1, ma_order=1, unbiased=False
167 fixed_params=fixed_params, unbiased=False
183 fixed_params=fixed_params, unbiased=False
300 initial_ar_order=22, unbiased=False,
338 endog, ar_order=1, ma_order=1, unbiased=None,
[all …]
|
| /dports/devel/py-hypothesis/hypothesis-6.28.0/src/hypothesis/internal/conjecture/ |
| H A D | floats.py | 95 unbiased = e - BIAS
96 if unbiased < 0:
97 return 10000 - unbiased
99 return unbiased
|
| /dports/math/R-cran-energy/energy/man/ |
| H A D | dcovu.Rd | 6 These functions compute unbiased estimators of squared distance
19 The unbiased (squared) dcov is inner product definition of
28 \code{dcovU} returns the unbiased estimator of squared dcov.
34 unbiased statistic, it is signed and we do not take the square root.
|
| H A D | dcovU_stats.Rd | 5 This function computes unbiased estimators of squared distance
17 The unbiased (squared) dcov is inner product definition of
31 unbiased statistic, it is signed and we do not take the square root.
|
| H A D | dcov2d.Rd | 7 correlation and distance covariance statistics. The U-statistic for dcov^2 is unbiased;
22 The unbiased (squared) dcov is documented in \code{dcovU}, for multivariate data in arbitrary, not …
25 …y)}{V_n = dCov_n^2(x, y)}, and if type="U", it returns the U-statistic, unbiased for \eqn{dCov^2(X…
|
| H A D | centering.Rd | 9 that are applied in unbiased distance covariance, bias
46 \code{pdcor} as well as the unbiased dCov and bias corrected
|
| /dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/tsa/arima/estimators/ |
| H A D | hannan_rissanen.py | 19 initial_ar_order=None, unbiased=None, argument
220 if unbiased is True:
234 elif unbiased is None:
236 unbiased = False
238 unbiased = p.is_stationary and p.is_invertible
241 if unbiased is True:
|
| /dports/math/octave-forge-stk/stk/inst/param/estim/ |
| H A D | stk_param_gls.m | 11 % also returns the associated unbiased estimate SIGMA2 of sigma^2, assu-
15 % SIGMA2 is actually the "best" unbiased estimate of sigma^2 :
24 % best estimate with respect to the quadratic risk, among all unbiased
75 % "best" unbiased estimate of sigma2 (best wrt the quadratic risk, among
76 % all unbiased estimates which are quadratic in the residuals)
|
| /dports/misc/mxnet/incubator-mxnet-1.9.0/3rdparty/tvm/python/tvm/relay/op/ |
| H A D | reduce.py | 317 def variance(data, axis=None, keepdims=False, exclude=False, unbiased=False): argument
349 return _make._variance(data, m, axis, keepdims, exclude, unbiased)
352 def std(data, axis=None, keepdims=False, exclude=False, unbiased=False): argument
384 return sqrt(_make._variance(data, m, axis, keepdims, exclude, unbiased))
|
| /dports/math/R/R-4.1.2/src/library/stats/man/ |
| H A D | cov.wt.Rd | 11 method = c("unbiased", "ML"))
43 By default, \code{method = "unbiased"},
46 unbiased estimate of the covariance matrix with divisor \eqn{(n - 1)}
55 cov.wt(xy, wt = w1) # i.e. method = "unbiased"
|
| /dports/math/libRmath/R-4.1.1/src/library/stats/man/ |
| H A D | cov.wt.Rd | 11 method = c("unbiased", "ML"))
43 By default, \code{method = "unbiased"},
46 unbiased estimate of the covariance matrix with divisor \eqn{(n - 1)}
55 cov.wt(xy, wt = w1) # i.e. method = "unbiased"
|
| /dports/math/octave-forge-nan/nan-3.6.1/inst/ |
| H A D | std.m | 8 % provides the square root of best unbiased estimator of the variance
12 % best unbiased estimator of the standard deviation (see [1])
24 % - provides an unbiased estimation of the S.D.
91 % square root if the best unbiased estimator of the variance
100 % best unbiased estimator of the mean
|
| H A D | skewness.m | 54 %if flag_implicit_unbiased_estim; %% ------- unbiased estimates -----------
60 R.VAR = R.SSQ0./n1; % variance (unbiased)
|
| /dports/math/openturns/openturns-1.18/python/test/ |
| H A D | t_GeneralLinearModelAlgorithm_std.expout | 19 covariance (reduced, unbiased)= AbsoluteExponential(scale=[0.1328], amplitude=[0.1956])
20 trend (reduced, unbiased)= [[-0.1034,1.014]]
|
| /dports/graphics/mirtk/MIRTK-2.0.0-122-g38210fa/Applications/src/ |
| H A D | average-measure.py | 76 def write_stats(out, x, w, sum_w=0., sum_w2=0., unbiased=False, digits=5): argument
84 if unbiased:
228 write_stats(f_out, x=values, w=roi, unbiased=args.unbiased, digits=args.digits)
255 …write_stats(f_out, x=values, w=roi, sum_w=sum_w, sum_w2=sum_w2, unbiased=args.unbiased, digits=arg…
|
| /dports/math/scilab/scilab-6.1.1/scilab/modules/signal_processing/tests/unit_tests/ |
| H A D | xcorr.dia.ref | 15 assert_checkalmostequal(c_ref./(7-abs(ind)),xcorr(x,"unbiased"));
20 [c,ind]=xcorr(x,3,"unbiased");
40 [c,ind]=xcorr(x,y,3,"unbiased");
|
| H A D | xcorr.tst | 16 assert_checkalmostequal(c_ref./(7-abs(ind)),xcorr(x,"unbiased"));
22 [c,ind]=xcorr(x,3,"unbiased");
46 [c,ind]=xcorr(x,y,3,"unbiased");
|
| /dports/misc/mxnet/incubator-mxnet-1.9.0/3rdparty/tvm/include/tvm/relay/attrs/ |
| H A D | reduce.h | 68 bool unbiased; member
91 TVM_ATTR_FIELD(unbiased).set_default(false).describe("Whether to use the unbiased estimation.");
|
| /dports/math/openturns/openturns-1.18/lib/test/ |
| H A D | t_GeneralLinearModelAlgorithm_std.expout | 14 covariance (reduced, unbiased)=class=AbsoluteExponential scale=class=Point name=Unnamed dimension=1…
15 trend (reduced, unbiased)=[[-0.1034,1.014]]
|
| /dports/math/p5-Statistics-Lite/Statistics-Lite-3.62/ |
| H A D | Changes | 20 - added unbiased versions
22 …estored to the sample or biased version of the formula; if you need the unbiased version, use stdd…
|
| /dports/misc/mxnet/incubator-mxnet-1.9.0/3rdparty/tvm/src/relay/op/tensor/ |
| H A D | reduce.cc | 566 bool unbiased = param->unbiased; in VarianceCompute() local
572 if (unbiased) { in VarianceCompute()
587 bool unbiased = false) { in MakeVariance() argument
592 attrs->unbiased = unbiased; in MakeVariance()
|
| /dports/math/libxsmm/libxsmm-1.16.3/src/ |
| H A D | libxsmm_math.c | 363 int sign, temp, unbiased, exponent, mantissa; in internal_math_sexp2() local
369 unbiased = (temp >> 23) - 127; /* exponent */ in internal_math_sexp2()
370 exponent = -unbiased; in internal_math_sexp2()
375 if (7 >= unbiased) { /* not a degenerated case */ in internal_math_sexp2()
378 if (0 > unbiased) { /* regular/main case */ in internal_math_sexp2()
394 for (i = 0; i < unbiased; ++i) { /* compute squares */ in internal_math_sexp2()
|
| /dports/finance/R-cran-PerformanceAnalytics/PerformanceAnalytics/man/ |
| H A D | CoMoments.Rd | 24 M3.MM(R, unbiased = FALSE, as.mat = TRUE, ...)
40 \item{unbiased}{TRUE/FALSE whether to use a correction to have an unbiased
|
| /dports/science/afni/afni-AFNI_21.3.16/src/matlab/ |
| H A D | VectStat.m | 20 % .S : the (unbiased) standard deviation of M(i,:)
75 Stat(i).S = std(M(i,igood),0); %unbiased estimator
|
| /dports/www/elgg/elgg-3.3.23/vendor/fzaninotto/faker/src/Faker/Provider/ |
| H A D | Biased.php | 38 protected static function unbiased() function in Faker\\Provider\\Biased
|