如果詞彙表中的術語第一次出現是複數怎麼辦?

如果詞彙表中的術語第一次出現是複數怎麼辦?

我正在 LaTeX 中使用套件術語表。在序言中我有

\newglossaryentry{error}
{
  name = error,
  description = {the difference between the actual value and the predicted value}
}

在文字中我有

$e$ 是 $nx 1$ 錯誤向量

我想要一個錯誤的詞彙表項目(單數)。

如果我使用 \gls{errors} ,它很明智地表示沒有條目。如果我使用 \gls{error}s 則不會出現術語表條目。

我怎樣才能做我想做的事?

這是一個 MWE(由於上述問題,它不起作用)。

\documentclass{book}

\usepackage{fancyvrb}%Verbatim
\usepackage[acronym]{glossaries}
\usepackage{natbib}
\usepackage{latexsym}
\usepackage{amssymb}
\usepackage{amsmath}
\usepackage[dvipdf]{graphicx}
\usepackage{mathptmx}
\usepackage{alltt}
\usepackage{color}
\usepackage{float}

\usepackage{fancyhdr}

\pagestyle{fancy}
\fancyhf{}
\fancyhead[LE,LO]{\thechapter}
\fancyhead[RE,RO]{\thesection}
\fancyfoot[CE,CO]{\thepage}

\pagestyle{plain}
\title{The General Linear Model: Assumptions, violations and remedies or What to do when your dependent variable won't behave}
\author{Peter Flom}

\makeglossaries

\newglossaryentry{error}
{
  name = error,
  description = {the difference between the actual value and the predicted value}
}

\begin{document}
\maketitle
 \addcontentsline{toc}{chapter}{Contents}
\pagenumbering{roman}
\tableofcontents
\listoffigures
\listoftables
\chapter*{Preface}\normalsize
  \addcontentsline{toc}{chapter}{Preface}
\pagestyle{plain}

This is a book about regression. 
\pagestyle{fancy}
\pagenumbering{arabic}



\chapter{Introduction: The General Linear Model and its Assumptions}
  \section{The model}
  The general linear model (GLM) subsumes linear regression and ANOVA (these models are equivalent, if you do not know why, see Appendix A; in this book I will use the regression framework). It is one of the most commonly used statistical methods, used in thousands of papers and analyses in every field of science and business. The idea is that we have one dependent (or target, or outcome) variable that we want to model as a linear function of one or more independent variables. The dependent variable (DV) must be continuous. The independent variables (IV) can be categorical or continuous. The model can be written:
  \[
    Y = b_0 + b_1x_1 + b_2x_2 + \dots b_px_p + e
  \]
  where there are p independent variables.
  In matrix terms (for all the matrix knowledge you will need in this book see appendix B)
  \[
    Y = XB + e
  \]
  where $Y$ is an $n x 1$ vector of dependent variable, $X$ is an $n x p$ matrix of independent variables, $B$ is a $p x 1$ vector of parameters to be estimated and $e$ is an $n x 1$ vector of \gls{errors}.


\chapter{Glossary}
\clearpage

\printglossary[type=\acronymtype]

\printglossary
\end{document}

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