我正在使用 LaTeX 中的术语表包。在序言中，我有
\newglossaryentry{error}
{
name = error,
description = {the difference between the actual value and the predicted value}
}
在文中我有
并且 $e$ 是 $nx 1$ 个误差向量
我想要一个关于错误（单数）的词汇表。
如果我使用 \gls{errors}，它会很明智地提示没有条目。如果我使用 \gls{error}s，则不会出现任何词汇表条目。
我怎样才能做我想做的事？
这是一个 MWE（由于上述问题，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}