- using R version 4.4.1 (2024-06-14)
- using platform: x86_64-pc-linux-gnu
- R was compiled by
gcc-14 (Debian 14.2.0-3) 14.2.0
GNU Fortran (Debian 14.2.0-3) 14.2.0
- running under: Debian GNU/Linux trixie/sid
- using session charset: UTF-8
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- this is package ‘GWRM’ version ‘2.1.0.4’
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See the install log for details.
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66 | \item \code{Y} {if requested (the default), the \code{y} vector used.}
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67 | \item \code{W} {the weights supplied, a vector of \code{1}s if none were.}
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68 | \item \code{covars} {names of the covariates in the model.}
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69 | \item \code{nobs} {number of observations.}
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70 | \item \code{covoffset} {a logical value specifying if an offset is present.}
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71 | \item \code{loglik} {the maximized log-likelihood.}
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72 | \item \code{aic} {a version of Akaike's \emph{An Information Criterion}, minus twice the maximized log-likelihood plus twice the number of parameters.}
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73 | \item \code{bic} {Bayesian Information Criterion, minus twice the maximized log-likelihood plus the number of parameters multiplied by the logarithm of the number of observations.}
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74 | \item \code{df.residual} {the residual degrees of freedom.}
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75 | \item \code{residuals} {the residuals in the final iteration of the fit.}
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76 | \item \code{coefficients} {a named vector of coefficients.}
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77 | \item \code{betaIIpars} {parameters estimates of the BetaII distribution.}
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78 | \item \code{betascoefs} {a vector of coefficients.}
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79 | \item \code{fitted.values} {the fitted mean values, obtained by transforming the linear predictors by the inverse of the link function.}
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80 | \item \code{hessian} {a symmetric matrix giving an estimate of the Hessian at the solution found in the optimization of the log-likelihood function.}
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81 | \item \code{cov} {an estimate of the covariance matrix of the model coefficients.}
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82 | \item \code{se} {a vector of the standard errors estimates of the estimated coefficients.}
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83 | \item \code{corr} {an estimate of the correlation matrix of the model coefficients.}
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84 | \item \code{code} {a code that indicates successful convergence of the fitter function used (see \code{nlm} and \code{optim} helps).}
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85 | \item \code{converged} {logical value that indicates if the optimization algorithms succesfull.}
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86 | \item \code{method} {the name of the fitter function used.}
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87 | \item \code{k} {if requested, the \code{k} value used.}
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88 | \item \code{kBool} {a logical value specifying whether there is a \code{k} value or it is estimated.}
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89 | \item \code{call} {the matched call.}
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90 | \item \code{formula} {the formula supplied.}
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91 | \item \code{terms} {the \code{terms} object used.}
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92 | \item \code{data} {the \code{data} argument.}
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93 | \item \code{offset} {the offset vector used.}
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94 | \item \code{control} {the value of the \code{control} argument used.}
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95 | \item \code{method} {the name of the fitter function used.}
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96 | \item \code{contrasts} {(where relevant) the contrasts used.}
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97 | \item \code{xlevels} {(where relevant) a record of the levels of the factors used in fitting.}
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- DONE
Status: 1 NOTE