checkRd: (-1) fitJSB.Rd:21: Lost braces
    21 | \item A sequence of four goodness-of-fit measures consist of Anderson-Darling (\code{AD}), Cram\'{e}er-von Misses (\code{CVM}), Kolmogorov-Smirnov (\code{KS}), and log-likelihood (\code{log-likelihood}) statistics.
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checkRd: (-1) fitWeibull.Rd:46: Lost braces
    46 | \item A sequence of goodness-of-fit measures consist of Akaike Information Criterion (\code{AIC}), Consistent Akaike Information Criterion (\code{CAIC}), Bayesian Information Criterion (\code{BIC}), Hannan-Quinn information criterion (\code{HQIC}), Anderson-Darling (\code{AD}), Cram\'{e}er-von Misses (\code{CVM}), Kolmogorov-Smirnov (\code{KS}), and log-likelihood (\code{log-likelihood}) statistics.}
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checkRd: (-1) fitbayesJSB.Rd:19: Lost braces
    19 | \item A sequence of four goodness-of-fit measures consist of Anderson-Darling (\code{AD}), Cram\'{e}er-von Misses (\code{CVM}), Kolmogorov-Smirnov (\code{KS}), and  log-likelihood (\code{log-likelihood}) statistics.
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checkRd: (-1) fitbayesWeibull.Rd:15: Lost braces
    15 | \item A sequence of four goodness-of-fit measures consist of Anderson-Darling (\code{AD}), Cram\'{e}er-von Misses (\code{CVM}), Kolmogorov-Smirnov (\code{KS}), and log-likelihood (\code{log-likelihood}) statistics.
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checkRd: (-1) fitgrouped1.Rd:32: Lost braces
    32 | Cram\'{e}er-von Misses (\code{CVM}), Kolmogorov-Smirnov (\code{KS}), and log-likelihood (\code{log-likelihood}) statistics.
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checkRd: (-1) fitgrouped2.Rd:27: Lost braces
    27 | \item A sequence of goodness-of-fit measures consist of Anderson-Darling (\code{AD}), Cram\'{e}er-von Misses (\code{CVM}), and Kolmogorov-Smirnov (\code{KS}) statistics.
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checkRd: (-1) fitgsm.Rd:17: Lost braces
    17 | \item A sequence of goodness-of-fit measures consist of Akaike Information Criterion (\code{AIC}), Consistent Akaike Information Criterion (\code{CAIC}), Bayesian Information Criterion (\code{BIC}), Hannan-Quinn information criterion (\code{HQIC}), Anderson-Darling (\code{AD}), Cram\'{e}er-von Misses (\code{CVM}), Kolmogorov-Smirnov (\code{KS}), and log-likelihood (\code{log-likelihood}) statistics.}
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checkRd: (-1) fitmixture.Rd:19: Lost braces
    19 | \item The second part involves a sequence of goodness-of-fit measures consist of Akaike Information Criterion (\code{AIC}), Consistent Akaike Information Criterion (\code{CAIC}), Bayesian Information Criterion (\code{BIC}), Hannan-Quinn information criterion (\code{HQIC}), Anderson-Darling (\code{AD}), Cram\'{e}er-von Misses (\code{CVM}), Kolmogorov-Smirnov (\code{KS}), and log-likelihood (\code{log-likelihood}) statistics.
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checkRd: (-1) fitmixturegrouped.Rd:28: Lost braces
    28 | \item A sequence of goodness-of-fit measures consist of Akaike Information Criterion (\code{AIC}), Consistent Akaike Information Criterion (\code{CAIC}), Bayesian Information Criterion (\code{BIC}), Hannan-Quinn information criterion (\code{HQIC}), Anderson-Darling (\code{AD}), Cram\'{e}er-von Misses (\code{CVM}), Kolmogorov-Smirnov (\code{KS}), and log-likelihood (\code{log-likelihood}) statistics.}
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checkRd: (-1) rmixture.Rd:6: Lost braces
     6 | where \eqn{K} is the number of components, \eqn{\theta_j}, for \eqn{j=1,\dots,K} is parameter space of the \eqn{j}-th component, i.e. \eqn{\theta_j=(\alpha_j,\beta_j)^{T}}, and \eqn{\Theta} is the whole parameter vector \eqn{\Theta=(\theta_1,\dots,\theta_K)^{T}}. Parameters \eqn{\alpha} and \eqn{\beta} are the shape and scale parameters or both are the shape parameters. In the latter case, parameters \eqn{\alpha} and \eqn{\beta} are called the first and second shape parameters, respectively. We note that the constants \eqn{\omega_j}s sum to one, i.e., \eqn{\sum_{j=1}^{K}\omega_j=1}. The families considered for the cdf \eqn{f} include Birnbaum-Saunders, Burr type XII, Chen, F, Fr{\'e}chet, Gamma, Gompertz, Log-normal, Log-logistic, Lomax, skew-normal, and Weibull.}
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