/dports/science/dalton/dalton-66052b3af5ea7225e31178bf9a8b031913c72190/basis/ecp_data/ |
H A D | pe_pp | 12 $ H, fitted from He 23 $ He, fitted from He 34 $ Li, fitted from Ne 47 $ Be, fitted from Ne 60 $ B, fitted from Ne 73 $ C, fitted from Ne 86 $ N, fitted from Ne 99 $ O, fitted from Ne 112 $ F, fitted from Ne 190 $ P, fitted from Ar [all …]
|
/dports/math/R-cran-forecast/forecast/man/ |
H A D | fitted.Arima.Rd | 4 \name{fitted.ARFIMA} 5 \alias{fitted.ARFIMA} 6 \alias{fitted.Arima} 7 \alias{fitted.forecast_ARIMA} 8 \alias{fitted.ar} 9 \alias{fitted.bats} 10 \alias{fitted.ets} 11 \alias{fitted.modelAR} 12 \alias{fitted.nnetar} 13 \alias{fitted.tbats} [all …]
|
/dports/finance/R-cran-fGarch/fGarch/man/ |
H A D | methods-fitted.Rd | 1 \name{fitted-methods} 7 \alias{fitted-methods} 8 \alias{fitted,ANY-method} 17 Extracts fitted values from a fitted GARCH object. 84 ## fitted - 86 fitted = fitted(fit) 87 head(fitted) 88 class(fitted) 92 fitted = slot(fit, "fitted") 93 head(fitted) [all …]
|
/dports/math/R-cran-forecast/forecast/tests/testthat/ |
H A D | test-refit.R | 12 expect_false(identical(fit$fitted, refit$fitted)) 18 expect_true(all.equal(fit$fitted, refit_same$fitted)) 28 expect_false(identical(fit$fitted, refit$fitted)) 35 expect_true(identical(fit$fitted, refit_same$fitted)) 43 expect_false(identical(fit$fitted, refit$fitted)) 49 expect_true(identical(fit$fitted, refit_same$fitted)) 58 expect_false(identical(fit$fitted, refit$fitted)) 63 expect_true(identical(fit$fitted, refit_same$fitted)) 72 expect_false(identical(fit$fitted, refit$fitted)) 116 expect_false(identical(fit$fitted, refit$fitted)) [all …]
|
H A D | test-hfitted.R | 7 h1 <- fitted(mod1, h = 1) 8 h2 <- fitted(mod1, h = 2) 16 h1 <- fitted(mod2, h = 1) 17 h2 <- fitted(mod2, h = 2) 22 h1 <- fitted(mod3, h = 1) 23 h2 <- fitted(mod3, h = 2) 40 h1 <- fitted(mod5, h = 1) 41 h2 <- fitted(mod5, h = 2)
|
/dports/math/R/R-4.1.2/src/library/stats/man/ |
H A D | fitted.values.Rd | 1 % File src/library/stats/man/fitted.values.Rd 6 \name{fitted} 9 fitted(object, \dots) 10 fitted.values(object, \dots) 12 \alias{fitted.values} 13 \alias{fitted} 14 \alias{fitted.default} 21 \code{fitted} is a generic function which extracts fitted values from 22 objects returned by modeling functions. \code{fitted.values} is an 26 should provide a \code{fitted} method. (Note that the generic is [all …]
|
/dports/math/libRmath/R-4.1.1/src/library/stats/man/ |
H A D | fitted.values.Rd | 1 % File src/library/stats/man/fitted.values.Rd 6 \name{fitted} 9 fitted(object, \dots) 10 fitted.values(object, \dots) 12 \alias{fitted.values} 13 \alias{fitted} 14 \alias{fitted.default} 21 \code{fitted} is a generic function which extracts fitted values from 22 objects returned by modeling functions. \code{fitted.values} is an 26 should provide a \code{fitted} method. (Note that the generic is [all …]
|
/dports/math/apache-commons-math/commons-math3-3.6.1-src/src/test/java/org/apache/commons/math3/optimization/fitting/ |
H A D | HarmonicFitterTest.java | 69 final double[] fitted = fitter.fit(); in testNoError() local 70 Assert.assertEquals(a, fitted[0], 1.0e-13); in testNoError() 71 Assert.assertEquals(w, fitted[1], 1.0e-13); in testNoError() 74 HarmonicOscillator ff = new HarmonicOscillator(fitted[0], fitted[1], fitted[2]); in testNoError() 96 final double[] fitted = fitter.fit(); 97 Assert.assertEquals(a, fitted[0], 7.6e-4); 98 Assert.assertEquals(w, fitted[1], 2.7e-3); 133 Assert.assertEquals(a, fitted[0], 1.2e-3); 134 Assert.assertEquals(w, fitted[1], 3.3e-3); 175 final double[] fitted = fitter.fit(); [all …]
|
/dports/math/apache-commons-math/commons-math3-3.6.1-src/src/test/java/org/apache/commons/math3/fitting/ |
H A D | HarmonicFitterTest.java | 53 final double[] fitted = fitter.fit(); in testNoError() local 54 Assert.assertEquals(a, fitted[0], 1.0e-13); in testNoError() 55 Assert.assertEquals(w, fitted[1], 1.0e-13); in testNoError() 58 HarmonicOscillator ff = new HarmonicOscillator(fitted[0], fitted[1], fitted[2]); in testNoError() 80 final double[] fitted = fitter.fit(); 81 Assert.assertEquals(a, fitted[0], 7.6e-4); 82 Assert.assertEquals(w, fitted[1], 2.7e-3); 117 Assert.assertEquals(a, fitted[0], 1.2e-3); 118 Assert.assertEquals(w, fitted[1], 3.3e-3); 159 final double[] fitted = fitter.fit(); [all …]
|
H A D | HarmonicCurveFitterTest.java | 53 final double[] fitted = fitter.fit(points.toList()); in testNoError() local 54 Assert.assertEquals(a, fitted[0], 1.0e-13); in testNoError() 55 Assert.assertEquals(w, fitted[1], 1.0e-13); in testNoError() 58 final HarmonicOscillator ff = new HarmonicOscillator(fitted[0], fitted[1], fitted[2]); in testNoError() 78 final double[] fitted = fitter.fit(points.toList()); 79 Assert.assertEquals(a, fitted[0], 7.6e-4); 80 Assert.assertEquals(w, fitted[1], 2.7e-3); 116 Assert.assertEquals(a, fitted[0], 1.2e-3); 117 Assert.assertEquals(w, fitted[1], 3.3e-3); 158 Assert.assertEquals(a, fitted[0], 7.6e-4); [all …]
|
/dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/base/tests/ |
H A D | test_predict.py | 22 fitted = res.fittedvalues.iloc[1:10:2] 25 pdt.assert_index_equal(pred.index, fitted.index) 63 fitted = res.fittedvalues.iloc[1:10:2] 67 assert_allclose(pred, fitted.values, rtol=1e-13) 74 pdt.assert_index_equal(pred.index, fitted.index) 124 fitted = res.fittedvalues.iloc[1:10:2] 125 offset = np.arange(len(fitted)) 126 fitted = fitted + offset 129 pdt.assert_index_equal(pred.index, fitted.index) 142 pdt.assert_index_equal(pred.index, fitted.index) [all …]
|
/dports/math/R-cran-VGAM/VGAM/man/ |
H A D | fittedvlm.Rd | 3 \alias{fitted.values.vlm} 14 fittedvlm(object, drop = FALSE, type.fitted = NULL, 37 \item{type.fitted}{ 96 generic function \code{fitted.values}. 110 \code{\link[stats]{fitted}}, 120 fitted(fit1) 126 head(fitted(fit2)) 135 head(fitted(fit3, type.fitted = "mean" )) # E(Y), which is the default 136 head(fitted(fit3, type.fitted = "pobs0")) # P(Y = 0) 137 head(fitted(fit3, type.fitted = "pstr0")) # Prob of a structural 0 [all …]
|
/dports/math/R-cran-NMF/NMF/man/ |
H A D | fitted.Rd | 2 \name{fitted} 3 \alias{fitted} 4 \alias{fitted-methods} 5 \alias{fitted,NMFfit-method} 6 \alias{fitted,NMF-method} 7 \alias{fitted,NMFns-method} 8 \alias{fitted,NMFOffset-method} 9 \alias{fitted,NMFstd-method} 12 fitted(object, ...) 14 \S4method{fitted}{NMFstd}(object, W, H, ...) [all …]
|
/dports/math/R-cran-sm/sm/inst/scripts/ |
H A D | bissell3.q | 18 glm.fitted<- beta*X 21 sm.fitted <- ((W %*% Y)/denom)*X 22 disp <- dev(Y,sm.fitted)/(length(Y)-1) 23 ts.orig <- (dev(Y,glm.fitted)-dev(Y,sm.fitted))/disp 29 yboot<-rpois(length(glm.fitted),glm.fitted) 30 sm.fitted <- ((W %*% yboot)/denom)*X 31 disp <- dev(yboot,sm.fitted)/(length(yboot)-1) 32 ts.boot <- (dev(yboot,glm.fitted)-dev(yboot,sm.fitted))/disp 34 lines(X, sm.fitted, lty=2,col=6)
|
/dports/science/py-segregation/segregation-2.1.0/segregation/batch/ |
H A D | batch_compute.py | 59 fitted = {} 65 fitted[each] = singlegroup_classes[each]( 74 fitted = pd.DataFrame.from_dict(fitted, orient="index").round(4) 75 fitted.columns = ["Statistic"] 76 fitted.index.name = "Name" 77 return fitted 97 fitted = {} 100 fitted = pd.DataFrame.from_dict(fitted, orient="index").round(4) 101 fitted.columns = ["Statistic"] 102 fitted.index.name = "Name" [all …]
|
/dports/finance/R-cran-vars/vars/man/ |
H A D | fitted.Rd | 1 \name{fitted} 3 \alias{fitted} 5 \alias{fitted.values} 7 \alias{fitted.varest} 9 \alias{fitted.vec2var} 16 Returns the fitted values of a VAR(p)-model for objects generated by 18 the fitted.values-method is applied to the list element 23 \method{fitted}{varest}(object, ...) 24 \method{fitted}{vec2var}(object, ...) 51 fitted(var.2c)
|
/dports/math/mlpack/mlpack-3.4.2/src/mlpack/core/dists/ |
H A D | regression_distribution.cpp | 29 arma::rowvec fitted; in Train() local 30 lr.Predict(observations.rows(1, observations.n_rows - 1), fitted); in Train() 31 err.Train(observations.row(0) - fitted); in Train() 51 arma::rowvec fitted; in Train() local 52 lr.Predict(observations.rows(1, observations.n_rows - 1), fitted); in Train() 53 err.Train(observations.row(0) - fitted, weights.t()); in Train() 63 arma::rowvec fitted; in Probability() local 64 rf.Predict(observation.rows(1, observation.n_rows-1), fitted); in Probability() 65 return err.Probability(observation(0)-fitted.t()); in Probability()
|
/dports/finance/R-cran-gmm/gmm/man/ |
H A D | fitted.Rd | 1 \name{fitted} 2 \alias{fitted.gel} 3 \alias{fitted.gmm} 6 …Method to extract the fitted values of the model estimated by \code{\link{gel}} or \code{\link{gmm… 9 \method{fitted}{gel}(object, ...) 10 \method{fitted}{gmm}(object, ...) 14 \item{...}{Other arguments when \code{fitted} is applied to an other class object} 18 …rns a matrix of the estimated mean \eqn{\hat{y}} in \code{g=y~x} as it is done by \code{fitted.lm}. 41 lines(fitted(res), col = 2) 55 lines(x, fitted(res), col = 2)
|
/dports/math/R-cran-gss/gss/man/ |
H A D | fitted.ssanova.Rd | 1 \name{fitted.ssanova} 2 \alias{fitted.ssanova} 4 \alias{fitted.gssanova} 8 Methods for extracting fitted values and residuals from smoothing 12 \method{fitted}{ssanova}(object, ...) 15 \method{fitted}{gssanova}(object, ...) 25 The fitted values for \code{"gssanova"} objects are on the link
|
/dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/examples/ |
H A D | ex_emplike_2.py | 25 fitted = elmodel.fit() variable 30 test0_1 = fitted.el_test(np.array([0]), np.array([0])) 34 test1 = fitted.el_test(np.array([4]), np.array([3])) 38 test2 = fitted.el_test(np.array([3, 4]), np.array([2, 3])) 43 ci_beta1 = fitted.conf_int_el(1) 48 print(fitted.rsquared) 50 print(fitted.params)
|
H A D | try_polytrend.py | 25 fitted = [sm.OLS(gdp, exog[:, :maxr]).fit().fittedvalues for maxr in variable 34 plt.plot(fitted[i]) 40 plt.plot(gdp - fitted[i]) 45 plt.plot(fitted[-1], lw=2, color='r') 46 plt.plot(fitted[0], lw=2, color='g') 50 plt.plot(gdp - fitted[-1], lw=2, color='r') 51 plt.plot(gdp - fitted[0], lw=2, color='g')
|
/dports/math/R-cran-Zelig/Zelig/man/ |
H A D | fitted-Zelig-method.Rd | 3 \name{fitted,Zelig-method} 4 \alias{fitted,Zelig-method} 5 \title{Method for extracting estimated fitted values from Zelig objects} 7 \S4method{fitted}{Zelig}(object, ...) 12 \item{...}{Additional parameters to be passed to fitted} 15 Method for extracting estimated fitted values from Zelig objects
|
/dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/nonparametric/ |
H A D | smoothers_lowess_old.py | 104 fitted = np.zeros(n) 112 fitted, weights = _lowess_initial_fit(x_copy, y_copy, k, n) 115 _lowess_robustify_fit(x_copy, y_copy, fitted, 118 out = np.array([x_copy, fitted]).T 154 fitted = np.zeros(n) 171 fitted[i] = beta[0] + beta[1]*x_copy[i] 176 return fitted, weights 204 def _lowess_robustify_fit(x_copy, y_copy, fitted, weights, k, n): argument 237 residual_weights -= fitted 256 fitted[i] = beta[0] + beta[1] * x_copy[i]
|
/dports/finance/R-cran-quantmod/quantmod/man/ |
H A D | fittedModel.Rd | 10 \alias{fitted.values.quantmod} 11 \alias{fitted.quantmod} 17 Extract and replace fitted models from 19 \code{buildModel}. All objects fitted 39 \method{fitted.values}{quantmod}(object, \dots) 41 \method{fitted}{quantmod}(object, \dots) 55 Most often used to extract the final fitted 60 Most common methods to apply to fitted objects 64 calling directly on the fitted object. 68 a fitted model to an object. This [all …]
|
/dports/math/R-cran-pbkrtest/pbkrtest/inst/doc/ |
H A D | coercion.R | 52 max(abs(fitted(new1) - fitted(mod1))) < eps 53 max(abs(fitted(new0a) - fitted(mod0))) < eps 54 max(abs(fitted(new0b) - fitted(mod0))) < eps
|