| /dports/math/gsl/gsl-2.7/fit/ |
| H A D | test.c | 55 double c0, c1, cov00, cov01, cov11, sumsq; in main() local
65 &c0, &c1, &cov00, &cov01, &cov11, &sumsq); in main()
79 double c0, c1, cov00, cov01, cov11, sumsq; in main() local
89 &c0, &c1, &cov00, &cov01, &cov11, &sumsq); in main()
107 double c1, cov11, sumsq; in main() local
113 gsl_fit_mul (x, xstride, y, ystride, noint1_n, &c1, &cov11, &sumsq); in main()
116 gsl_test_rel (cov11, expected_cov11, 1e-10, "noint1 gsl_fit_mul cov11") ; in main()
121 double c1, cov11, sumsq; in main() local
143 double c1, cov11, sumsq; in main() local
149 gsl_fit_mul (x, xstride, y, ystride, noint2_n, &c1, &cov11, &sumsq); in main()
[all …]
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| H A D | gsl_fit.h | 42 double * cov00, double * cov01, double * cov11,
51 double * cov00, double * cov01, double * cov11,
57 const double cov00, const double cov01, const double cov11,
65 double * cov11,
73 double * cov11,
80 const double cov11,
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| H A D | linear.c | 199 const double cov00, const double cov01, const double cov11, in gsl_fit_linear_est() argument
203 *y_err = sqrt (cov00 + x * (2 * cov01 + cov11 * x)); in gsl_fit_linear_est()
340 const double c1, const double cov11, in gsl_fit_mul_est() argument
344 *y_err = sqrt (cov11) * fabs (x); in gsl_fit_mul_est()
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| /dports/audio/praat/praat-6.2.03/external/gsl/ |
| H A D | gsl_fit.h | 42 double * cov00, double * cov01, double * cov11,
51 double * cov00, double * cov01, double * cov11,
57 const double cov00, const double cov01, const double cov11,
65 double * cov11,
73 double * cov11,
80 const double cov11,
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| H A D | gsl_fit__linear.c | 199 const double cov00, const double cov01, const double cov11,
203 *y_err = sqrt (cov00 + x * (2 * cov01 + cov11 * x));
340 const double c1, const double cov11,
344 *y_err = sqrt (cov11) * fabs (x);
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| /dports/math/gsl/gsl-2.7/doc/examples/ |
| H A D | fitting.c | 12 double c0, c1, cov00, cov01, cov11, chisq; in main() local
15 &c0, &c1, &cov00, &cov01, &cov11, in main()
21 cov00, cov01, cov01, cov11); in main()
37 cov00, cov01, cov11, in main()
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| /dports/math/p5-Math-GSL/Math-GSL-0.43/pod/ |
| H A D | Fit.pod | 43 returned via the parameters (cov00, cov01, cov11). The sum of squares of the
48 cov00, cov01, cov11 and sumsq.
59 cov11). The weighted sum of squares of the residuals from the best-fit line,
61 order : 0 if the operation succeeded, 1 otherwise, c0, c1, cov00, cov01, cov11
64 =item gsl_fit_linear_est($x, $c0, $c1, $cov00, $cov01, $cov11)
67 their covariance $cov00, $cov01, $cov11 to compute the fitted function y and
78 the points around the best-fit line and returned via the parameter cov11. The
81 succeeded, 1 otherwise, c1, cov11 and sumsq.
91 and returned via the parameter cov11. The weighted sum of squares of the
94 otherwise, c1, cov11 and sumsq.
[all …]
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| /dports/math/p5-Math-GSL/Math-GSL-0.43/pm/Math/GSL/ |
| H A D | Fit.pm.1.15 | 152 returned via the parameters (cov00, cov01, cov11). The sum of squares of the
157 cov00, cov01, cov11 and sumsq.
168 cov11). The weighted sum of squares of the residuals from the best-fit line,
173 =item gsl_fit_linear_est($x, $c0, $c1, $cov00, $cov01, $cov11)
176 their covariance $cov00, $cov01, $cov11 to compute the fitted function y and
187 the points around the best-fit line and returned via the parameter cov11. The
190 succeeded, 1 otherwise, c1, cov11 and sumsq.
200 and returned via the parameter cov11. The weighted sum of squares of the
203 otherwise, c1, cov11 and sumsq.
205 =item gsl_fit_mul_est($x, $c1, $cov11)
[all …]
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| H A D | Fit.pm.2.7 | 152 returned via the parameters (cov00, cov01, cov11). The sum of squares of the
157 cov00, cov01, cov11 and sumsq.
168 cov11). The weighted sum of squares of the residuals from the best-fit line,
173 =item gsl_fit_linear_est($x, $c0, $c1, $cov00, $cov01, $cov11)
176 their covariance $cov00, $cov01, $cov11 to compute the fitted function y and
187 the points around the best-fit line and returned via the parameter cov11. The
190 succeeded, 1 otherwise, c1, cov11 and sumsq.
200 and returned via the parameter cov11. The weighted sum of squares of the
203 otherwise, c1, cov11 and sumsq.
205 =item gsl_fit_mul_est($x, $c1, $cov11)
[all …]
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| H A D | Fit.pm.2.3 | 152 returned via the parameters (cov00, cov01, cov11). The sum of squares of the
157 cov00, cov01, cov11 and sumsq.
168 cov11). The weighted sum of squares of the residuals from the best-fit line,
173 =item gsl_fit_linear_est($x, $c0, $c1, $cov00, $cov01, $cov11)
176 their covariance $cov00, $cov01, $cov11 to compute the fitted function y and
187 the points around the best-fit line and returned via the parameter cov11. The
190 succeeded, 1 otherwise, c1, cov11 and sumsq.
200 and returned via the parameter cov11. The weighted sum of squares of the
203 otherwise, c1, cov11 and sumsq.
205 =item gsl_fit_mul_est($x, $c1, $cov11)
[all …]
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| H A D | Fit.pm.2.6 | 152 returned via the parameters (cov00, cov01, cov11). The sum of squares of the
157 cov00, cov01, cov11 and sumsq.
168 cov11). The weighted sum of squares of the residuals from the best-fit line,
173 =item gsl_fit_linear_est($x, $c0, $c1, $cov00, $cov01, $cov11)
176 their covariance $cov00, $cov01, $cov11 to compute the fitted function y and
187 the points around the best-fit line and returned via the parameter cov11. The
190 succeeded, 1 otherwise, c1, cov11 and sumsq.
200 and returned via the parameter cov11. The weighted sum of squares of the
203 otherwise, c1, cov11 and sumsq.
205 =item gsl_fit_mul_est($x, $c1, $cov11)
[all …]
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| H A D | Fit.pm.1.16 | 152 returned via the parameters (cov00, cov01, cov11). The sum of squares of the
157 cov00, cov01, cov11 and sumsq.
168 cov11). The weighted sum of squares of the residuals from the best-fit line,
173 =item gsl_fit_linear_est($x, $c0, $c1, $cov00, $cov01, $cov11)
176 their covariance $cov00, $cov01, $cov11 to compute the fitted function y and
187 the points around the best-fit line and returned via the parameter cov11. The
190 succeeded, 1 otherwise, c1, cov11 and sumsq.
200 and returned via the parameter cov11. The weighted sum of squares of the
203 otherwise, c1, cov11 and sumsq.
205 =item gsl_fit_mul_est($x, $c1, $cov11)
[all …]
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| H A D | Fit.pm.2.2.1 | 152 returned via the parameters (cov00, cov01, cov11). The sum of squares of the
157 cov00, cov01, cov11 and sumsq.
168 cov11). The weighted sum of squares of the residuals from the best-fit line,
173 =item gsl_fit_linear_est($x, $c0, $c1, $cov00, $cov01, $cov11)
176 their covariance $cov00, $cov01, $cov11 to compute the fitted function y and
187 the points around the best-fit line and returned via the parameter cov11. The
190 succeeded, 1 otherwise, c1, cov11 and sumsq.
200 and returned via the parameter cov11. The weighted sum of squares of the
203 otherwise, c1, cov11 and sumsq.
205 =item gsl_fit_mul_est($x, $c1, $cov11)
[all …]
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| H A D | Fit.pm.2.4 | 152 returned via the parameters (cov00, cov01, cov11). The sum of squares of the
157 cov00, cov01, cov11 and sumsq.
168 cov11). The weighted sum of squares of the residuals from the best-fit line,
173 =item gsl_fit_linear_est($x, $c0, $c1, $cov00, $cov01, $cov11)
176 their covariance $cov00, $cov01, $cov11 to compute the fitted function y and
187 the points around the best-fit line and returned via the parameter cov11. The
190 succeeded, 1 otherwise, c1, cov11 and sumsq.
200 and returned via the parameter cov11. The weighted sum of squares of the
203 otherwise, c1, cov11 and sumsq.
205 =item gsl_fit_mul_est($x, $c1, $cov11)
[all …]
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| H A D | Fit.pm.2.5 | 152 returned via the parameters (cov00, cov01, cov11). The sum of squares of the
157 cov00, cov01, cov11 and sumsq.
168 cov11). The weighted sum of squares of the residuals from the best-fit line,
173 =item gsl_fit_linear_est($x, $c0, $c1, $cov00, $cov01, $cov11)
176 their covariance $cov00, $cov01, $cov11 to compute the fitted function y and
187 the points around the best-fit line and returned via the parameter cov11. The
190 succeeded, 1 otherwise, c1, cov11 and sumsq.
200 and returned via the parameter cov11. The weighted sum of squares of the
203 otherwise, c1, cov11 and sumsq.
205 =item gsl_fit_mul_est($x, $c1, $cov11)
[all …]
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| H A D | Fit.pm.2.0 | 152 returned via the parameters (cov00, cov01, cov11). The sum of squares of the
157 cov00, cov01, cov11 and sumsq.
168 cov11). The weighted sum of squares of the residuals from the best-fit line,
173 =item gsl_fit_linear_est($x, $c0, $c1, $cov00, $cov01, $cov11)
176 their covariance $cov00, $cov01, $cov11 to compute the fitted function y and
187 the points around the best-fit line and returned via the parameter cov11. The
190 succeeded, 1 otherwise, c1, cov11 and sumsq.
200 and returned via the parameter cov11. The weighted sum of squares of the
203 otherwise, c1, cov11 and sumsq.
205 =item gsl_fit_mul_est($x, $c1, $cov11)
[all …]
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| H A D | Fit.pm.2.1 | 152 returned via the parameters (cov00, cov01, cov11). The sum of squares of the
157 cov00, cov01, cov11 and sumsq.
168 cov11). The weighted sum of squares of the residuals from the best-fit line,
173 =item gsl_fit_linear_est($x, $c0, $c1, $cov00, $cov01, $cov11)
176 their covariance $cov00, $cov01, $cov11 to compute the fitted function y and
187 the points around the best-fit line and returned via the parameter cov11. The
190 succeeded, 1 otherwise, c1, cov11 and sumsq.
200 and returned via the parameter cov11. The weighted sum of squares of the
203 otherwise, c1, cov11 and sumsq.
205 =item gsl_fit_mul_est($x, $c1, $cov11)
[all …]
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| H A D | Fit.pm.2.2 | 152 returned via the parameters (cov00, cov01, cov11). The sum of squares of the
157 cov00, cov01, cov11 and sumsq.
168 cov11). The weighted sum of squares of the residuals from the best-fit line,
173 =item gsl_fit_linear_est($x, $c0, $c1, $cov00, $cov01, $cov11)
176 their covariance $cov00, $cov01, $cov11 to compute the fitted function y and
187 the points around the best-fit line and returned via the parameter cov11. The
190 succeeded, 1 otherwise, c1, cov11 and sumsq.
200 and returned via the parameter cov11. The weighted sum of squares of the
203 otherwise, c1, cov11 and sumsq.
205 =item gsl_fit_mul_est($x, $c1, $cov11)
[all …]
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| /dports/math/qtiplot-doc/qtiplot-0.9.8.9/qtiplot/src/analysis/ |
| H A D | PolynomialFit.cpp | 304 double c0, c1, cov00, cov01, cov11; in fit() local
306 gsl_fit_linear(d_x, 1, d_y, 1, d_n, &c0, &c1, &cov00, &cov01, &cov11, &chi_2); in fit()
308 gsl_fit_wlinear(d_x, 1, d_w, 1, d_y, 1, d_n, &c0, &c1, &cov00, &cov01, &cov11, &chi_2); in fit()
315 gsl_matrix_set(covar, 1, 1, cov11); in fit()
410 double c1, cov11; in fit() local
412 gsl_fit_mul(d_x, 1, d_y, 1, d_n, &c1, &cov11, &chi_2); in fit()
414 gsl_fit_wmul(d_x, 1, d_w, 1, d_y, 1, d_n, &c1, &cov11, &chi_2); in fit()
418 gsl_matrix_set(covar, 0, 0, cov11); in fit()
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| /dports/math/py-pygsl/pygsl-2.3.0/src/callback/ |
| H A D | gsl_multifit.i | 198 double * cov11,
329 double * cov00, double * cov01, double * cov11,
338 double * cov00, double * cov01, double * cov11,
355 double * cov11,
363 double * cov11,
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| /dports/astro/siril/siril/src/gui/ |
| H A D | linear_match.c | 41 double c0, c1, cov00, cov01, cov11, sumsq; in find_linear_coeff_ushort() local
76 gsl_fit_linear(x, 1, y, 1, count, &c0, &c1, &cov00, &cov01, &cov11, &sumsq); in find_linear_coeff_ushort()
89 double c0, c1, cov00, cov01, cov11, sumsq; in find_linear_coeff_float() local
121 gsl_fit_linear(x, 1, y, 1, count, &c0, &c1, &cov00, &cov01, &cov11, &sumsq); in find_linear_coeff_float()
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| /dports/science/scidavis/scidavis-2.4.0/libscidavis/src/ |
| H A D | PolynomialFit.cpp | 253 double c0, c1, cov00, cov01, cov11; in fit() local
260 gsl_fit_linear(d_x, 1, d_y, 1, d_n, &c0, &c1, &cov00, &cov01, &cov11, &chi_2); in fit()
262 gsl_fit_wlinear(d_x, 1, weights, 1, d_y, 1, d_n, &c0, &c1, &cov00, &cov01, &cov11, &chi_2); in fit()
271 gsl_matrix_set(covar, 1, 1, cov11); in fit()
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| /dports/science/kst2/kst-plot-38eddb5322a1d557f9d86ea95d456d76272941e3/src/plugins/fits/linear_unweighted/ |
| H A D | fitlinear_unweighted.cpp | 184 double cov11 = 0.0; in algorithm() local
204 … pInputs[XVALUES], 1, pInputs[YVALUES], 1, iLength, &c0, &c1, &cov00, &cov01, &cov11, &dSumSq ) ) { in algorithm()
206 gsl_fit_linear_est( pInputs[XVALUES][i], c0, c1, cov00, cov01, cov11, &y, &yErr ); in algorithm()
217 outputVectorYCovariance->raw_V_ptr()[2] = cov11; in algorithm()
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| /dports/science/kst2/kst-plot-38eddb5322a1d557f9d86ea95d456d76272941e3/src/plugins/fits/linear_weighted/ |
| H A D | fitlinear_weighted.cpp | 214 double cov11 = 0.0; in algorithm() local
221 … pInputs[WEIGHTS], 1, pInputs[YVALUES], 1, iLength, &c0, &c1, &cov00, &cov01, &cov11, &dSumSq ) ) { in algorithm()
223 gsl_fit_linear_est( pInputs[XVALUES][i], c0, c1, cov00, cov01, cov11, &y, &yErr ); in algorithm()
234 outputVectorYCovariance->raw_V_ptr()[2] = cov11; in algorithm()
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| /dports/math/p5-Math-GSL/Math-GSL-0.43/t/ |
| H A D | Fit.t | 104 ok(is_similar_relative($got[5], $expected_cov11, 1e-10), "norris gsl_fit_wlinear cov11");
138 ok(is_similar_relative($got[2], $expected_cov11, 1e-10), "noint1 gsl_fit_mul cov11");
172 ok(is_similar_relative($got[2], $expected_cov11, 1e-10), "noint1 gsl_fit_wmul cov11");
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