+ LV-j^RIt^RIHt^RIHt.ROt.ROt]!]RRR1,4t]!]RRR1,4tRt .R Ot .R Ot ]!] RRR1,4t ]!] RRR1,4t RtR#) N)poly1d)betac\P!V4pVPp\P!V4P \P 4pRpVR8pVR8Hp\P !V4V8pW4,V,(pW,pW,p\P!V4p \PW&\PW&VP^8d\V4\V4, W&VP^8dNRV^,, RR^V,,, \V^,V^,4, ,W&V PV4p V #)aVariance of the Tukey Lambda distribution. Parameters ---------- lam : array_like The lambda values at which to compute the variance. Returns ------- v : ndarray The variance. For lam < -0.5, the variance is not defined, so np.nan is returned. For lam = 0.5, np.inf is returned. Notes ----- In an interval around lambda=0, this function uses the [4,4] Pade approximation to compute the variance. Otherwise it uses the standard formula (https://en.wikipedia.org/wiki/Tukey_lambda_distribution). The Pade approximation is used because the standard formula has a removable discontinuity at lambda = 0, and does not produce accurate numerical results near lambda = 0. g333333?g@?g)npasarrayshape atleast_1dastypefloat64abs empty_likenaninfsize_tukeylambda_var_p_tukeylambda_var_qrreshape) lamshp thresholdlow_mask neghalf_mask small_maskreg_masksmallregvs & o/Volumes/fast/ai/experiments/ui-tars-smoke/.venv/lib/python3.14/site-packages/scipy/stats/_tukeylambda_stats.pytukeylambda_variancer +s$. **S/C ))C --  # #BJJ /CI TzH$;Ly(J(:56H OE -C cA&&AKffAO zzA~*514Fu4MM  xx!|S!V|sQW}(=(,S1WcAg(>)?@  #A Hc\P!V4pVPp\P!V4P \P 4pRpVR8pVR8Hp\P !V4V8pW4,V,(pW,pW,p\P!V4p \PW&\PW&VP^8d\V4\V4, W&VP^8dR^V,^,, ^\^V,^,V^,4,, ^\^V,^,^V,^,4,,p ^R^V,^,, \V^,V^,4, ^,,p W, ^, W&V PV4p V #)a*Kurtosis of the Tukey Lambda distribution. Parameters ---------- lam : array_like The lambda values at which to compute the variance. Returns ------- v : ndarray The variance. For lam < -0.25, the variance is not defined, so np.nan is returned. For lam = 0.25, np.inf is returned. g)\(?rgп)rrr r r r r rrrr_tukeylambda_kurt_p_tukeylambda_kurt_qrr) rrrr negqrtr_maskrrrrknumerdenoms & rtukeylambda_kurtosisr)s| **S/C ))C --  # #BJJ /CIU{H%r2s8-? /"56/"569 z?A 1$B$781$B$784 r!