在我的文档中的某些地方,我遇到了这个 \hbox full 错误,导致文字在边距的右侧突出。我已插入以下代码。
我现在意识到当我尝试这个代码块时乳胶基底,它看起来很好,即使我使用相同的几何代码,那里的线条似乎变得更长了。
我想这是因为我没有使用\documentclass{article}
但是这个模板https://www.latextemplates.com/template/masters-doctoral-thesis。也许这会让人很难提供帮助,但我还是想提出这个问题,希望能得到一些建议。
谢谢。
\documentclass{article}
\RequirePackage{geometry}
\geometry{
headheight=4ex,
includehead,
includefoot
}
\geometry{
paper=a4paper, % Change to letterpaper for US letter
inner=2.5cm, % Inner margin
outer=4.8cm, % Outer margin
bindingoffset=.5cm, % Binding offset
top=1.5cm, % Top margin
bottom=1.5cm, % Bottom margin
}
\begin{document}
Traditionally in Econometrics, statistical models such as
Auto-Regressive (AR) and Generalized Autoregressive
Conditional Heteroskedasticity (GARCH) models have been
used to estimate forecasts of time series.
\end{document}
答案1
我认为你还有更多类似的东西
\documentclass[12pt,draft]{article}
\begin{document}
Traditionally in Econometrics, statistical models such as Auto-Regressive
(AR) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH)
models have been used to estimate forecasts of time series.
\end{document}
超出 12pt(标有选项规则draft
)
一般来说,您可以在 TeX 的连字中添加更多技术词汇,但您实际上无法对 GARCH 进行连字。
您可以sloppy
通过拉伸空间来避免盒子过满:
\documentclass[12pt,draft]{article}
\begin{document}
\begin{sloppypar}
Traditionally in Econometrics, statistical models such as Auto-Regressive
(AR) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH)
models have been used to estimate forecasts of time series.
\end{sloppypar}
\end{document}
但 TeX 警告
Underfull \hbox (badness 3954) in paragraph at lines 7--8
但这显然也不太好。
你可以使用微打字机(这通常可以解决问题)
\documentclass[12pt,draft]{article}
\usepackage{microtype}
\begin{document}
Traditionally in Econometrics, statistical models such as Auto-Regressive
(AR) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH)
models have been used to estimate forecasts of time series.
\end{document}
这是超额的 2pt,如果您删除规则,您可能会决定接受看起来不太糟糕的结果draft
。
如果做不到这一点,你可以重新措辞一点,或者当你真的完成所有的编辑时,对空间进行微观管理,例如
\documentclass[12pt,draft]{article}
\usepackage{microtype}
\begin{document}
Traditionally in Econometrics, statistical models such as Auto-Regressive
(AR)\hspace{-.3pt} and Generalized Autoregressive Conditional Heteroskedasticity
\!(GARCH) models have been used to estimate forecasts of time series.
\end{document}
没有警告: