有人能帮忙把这个表格放到一页吗？
\begin{table}
\centering
\begin{table}[h]
\begin{tabular}{llllcl}
\tiny System:INFLATION AND UNEMPLOYMENT Estimation\\ \tiny Method: Least Squares\\ \tiny Sample: 1989 2014\\
\tiny Included observations: 26 \\
\tiny Total system (balanced) observations 52\\ \hline\hline &\tiny Coefficient &\tiny Std. Error &\tiny t-Statistic &\tiny Prob.\\ \hline\hline
\tiny C(1) &\tiny 0.262395 &\tiny 0.364940 &\tiny 0.719009 &\tiny 0.4814\\
\tiny C(2) &\tiny -0.595551 &\tiny 0.622512 &\tiny -0.956690 &\tiny 0.3514\\
\tiny C(3) &\tiny 0.279303 &\tiny 0.515167 &\tiny 0.542160 &\tiny 0.5944\\
\tiny C(4) &\tiny 0.093994 &\tiny 0.621750 &\tiny 0.151177 &\tiny 0.8815\\
\tiny C(5) &\tiny -0.442089 &\tiny 0.436318 &\tiny -1.013228 &\tiny 0.3244\\
\tiny C(6) &\tiny 1.575771 &\tiny 2.109222 &\tiny 0.747086 &\tiny 0.4647\\
\tiny C(7) &\tiny -4.662746 &\tiny 5.343604 &\tiny -0.872585 &\tiny 0.3944\\
\tiny C(8) &\tiny 2.824077 &\tiny 3.638512 &\tiny 0.776163 &\tiny 0.4477\\
\tiny C(9) &\tiny 0.176143 &\tiny 0.105336 &\tiny 1.672193 &\tiny 0.1118\\
\tiny C(10) &\tiny 0.157414 &\tiny 0.115267 &\tiny 1.365650 &\tiny 0.1889\\
\tiny C(11) \tiny &\tiny 0.325583 \tiny &\tiny 0.133983 &\tiny 2.430036 \tiny &\tiny 0.0258\\
\tiny C(12) &\tiny -0.044040 &\tiny0.175836 &\tiny -0.250462 &\tiny 0.8051\\
\tiny C(13) &\tiny 0.290630 &\tiny 0.232195 &\tiny 1.251663 &\tiny 0.2267\\
\tiny C(14) &\tiny 0.008564 &\tiny 0.193656 &\tiny 0.044225 &\tiny 0.9652\\
\tiny C(15) &\tiny 0.387795 &\tiny 0.165762 &\tiny2.339464 &\tiny 0.0310\\
\tiny C(16) &\tiny 0.243521 &\tiny 0.306769 &\tiny 0.793826 &\tiny 0.4376\\
\tiny C(17) &\tiny 4.818044 &\tiny 6.983893 &\tiny 0.689879 &\tiny 0.4991\\
\tiny C(18) &\tiny 1.064356 &\tiny 1.132110 &\tiny 0.940152 &\tiny 0.3596\\
\tiny C(19) &\tiny -1.150959 &\tiny 1.931147 &\tiny -0.595998 &\tiny 0.5586\\
\tiny C(20) &\tiny 0.654313 &\tiny 1.598142 &\tiny 0.409421 &\tiny 0.6871\\
\tiny C(21) &\tiny -0.595249 &\tiny 1.928781 &\tiny -0.308614 &\tiny 0.7612\\
\tiny C(22) &\tiny -1.357195 &\tiny 1.353537 &\tiny -1.002702 &\tiny 0.3293\\
\tiny C(23) &\tiny 4.566426 &\tiny 6.543192 &\tiny 0.697890 &\tiny 0.4942\\
\tiny C(24) &\tiny -20.04091 &\tiny 16.57683 &\tiny -1.208971 &\tiny 0.2423\\
\tiny C(25) &\tiny 14.40853 &\tiny 11.28733 &\tiny 1.276523 &\tiny 0.2180\\
\tiny C(26) &\tiny -0.175476 &\tiny 0.326772 &\tiny -0.536997 &\tiny 0.5978\\
\tiny C(27) &\tiny 0.381407 &\tiny 0.357579 &\tiny 1.066639 &\tiny 0.3002\\
\tiny C(28) &\tiny 0.158697 &\tiny 0.415639 &\tiny 0.381815 &\tiny 0.7071\\
\tiny C(29) &\tiny -1.169850 &\tiny 0.545476 &\tiny -2.144640 &\tiny 0.0459\\
\tiny C(30) &\tiny 0.600688 &\tiny 0.720311 &\tiny 0.833929 &\tiny 0.4153\\
\tiny C(31) &\tiny 0.764571 &\tiny 0.600755 &\tiny 1.272683 &\tiny 0.2193\\
\tiny C(32) &\tiny 1.138401 &\tiny 0.514224 &\tiny 2.213823 &\tiny 0.0400\\
\tiny C(33) &\tiny -0.139137 &\tiny 0.951653 &\tiny -0.146206 &\tiny 0.8854\\
\tiny C(34) &\tiny 10.13866 &\tiny 21.66531 &\tiny 0.467967 &\tiny 0.6454\\ \hline\hline
\tiny Determinant residual covariance &\tiny 19.24770\\ \hline\hline
\tiny \bf UNT
\tiny Observations: 26\\
\tiny R-squared &\tiny 0.880742 &\tiny Mean dependent var &\tiny 4.645045\\
\tiny Adjusted R-squared &\tiny 0.668727 &\tiny S.D. dependent var &\tiny 3.567955\\
\tiny S.E. of regression &\tiny 2.053583 &\tiny Sum squared resid &\tiny 37.95483\\
\tiny Durbin-Watson stat &\tiny 1.507160\\ \hline\hline
\tiny\bf INF
\tiny Observations: 26\\
\tiny R-squared &\tiny 0.839385 &\tiny Mean dependent var &\tiny 1.873077\\
\tiny Adjusted R-squared &\tiny 0.553847 &\tiny S.D. dependent var &\tiny 9.537570\\
\tiny S.E. of regression &\tiny 6.370588 &\tiny Sum squared resid &\tiny 365.2596\\
\tiny Durbin-Watson stat &\tiny 2.092647\\ \hline
\end{subtable}%
\end{tabular}
\end{table}
\end{document}
答案1
216 [!]\tiny指令是不需要的。请删除该\end{subtable}指令。我建议您将单个大型tabular环境拆分为两个单独的环境：第一个环境应包含 5 个标题行和 34 个回归量的估计值，第二个环境应包含回归的汇总统计数据。将材料拆分为两个单独的tabular环境可以更轻松地更紧凑地组织信息。
我还想建议您将数字数据与各自的小数点对齐；这可以通过使用包S的列类型来实现siunitx。后者还允许您对数字进行四舍五入，并自动在小数点后显示更少的数字。（您真的需要在小数点后显示 6 位吗？）最后，五个标题行中的材料不应与第一行中的其余材料对齐tabular。
另外：我忍不住要对本表中显示的回归结果发表一些评论。尽管我不知道因变量或自变量是什么，但我确实发现 34 个回归量中只有 4 个单独具有统计显著性，这可能令人担忧。其他 30 个回归量中的大多数要么毫无价值，要么（几乎）多重共线？对只有 52 个观测值的样本进行 34 个回归量的回归分析，会引发不止几个危险信号。我希望您的论文能够解决这些问题。
\documentclass{article}
\usepackage[a4paper,margin=2.5cm]{geometry} % set page size parameters
\usepackage{booktabs}
\usepackage[group-digits=false,
round-mode=places, % turn on automatic rounding
round-precision=5]{siunitx}
\newcommand\ml[1]{\multicolumn{5}{l}{#1}} % shortcut macro, for header lines
\begin{document}
\begin{table}[p]
\centering
\begin{tabular}{lS[table-format=-2.5]
S[table-format= 2.5]
S[table-format=-1.5]
S[table-format= 1.4,round-mode=off] }
\ml{System: INFLATION AND UNEMPLOYMENT} \\
\ml{Estimation Method: Least Squares} \\
\ml{Sample: 1989--2014}\\
\ml{Included observations: 26}\\
\ml{Total system (balanced) observations: 52}\\
\addlinespace
\toprule
& {\ \ Coeff.} & {Std.\ Err.} & {t-Stat.} & {Prob.}\\
\midrule
C(1) & 0.262395 & 0.364940 & 0.719009 & 0.4814\\
C(2) & -0.595551 & 0.622512 & -0.956690 & 0.3514\\
C(3) & 0.279303 & 0.515167 & 0.542160 & 0.5944\\
C(4) & 0.093994 & 0.621750 & 0.151177 & 0.8815\\
C(5) & -0.442089 & 0.436318 & -1.013228 & 0.3244\\
C(6) & 1.575771 & 2.109222 & 0.747086 & 0.4647\\
C(7) & -4.662746 & 5.343604 & -0.872585 & 0.3944\\
C(8) & 2.824077 & 3.638512 & 0.776163 & 0.4477\\
C(9) & 0.176143 & 0.105336 & 1.672193 & 0.1118\\
C(10) & 0.157414 & 0.115267 & 1.365650 & 0.1889\\
C(11) & 0.325583 & 0.133983 & 2.430036 & 0.0258\\
C(12) & -0.044040 &0.175836 & -0.250462 & 0.8051\\
C(13) & 0.290630 & 0.232195 & 1.251663 & 0.2267\\
C(14) & 0.008564 & 0.193656 & 0.044225 & 0.9652\\
C(15) & 0.387795 & 0.165762 &2.339464 & 0.0310\\
C(16) & 0.243521 & 0.306769 & 0.793826 & 0.4376\\
C(17) & 4.818044 & 6.983893 & 0.689879 & 0.4991\\
C(18) & 1.064356 & 1.132110 & 0.940152 & 0.3596\\
C(19) & -1.150959 & 1.931147 & -0.595998 & 0.5586\\
C(20) & 0.654313 & 1.598142 & 0.409421 & 0.6871\\
C(21) & -0.595249 & 1.928781 & -0.308614 & 0.7612\\
C(22) & -1.357195 & 1.353537 & -1.002702 & 0.3293\\
C(23) & 4.566426 & 6.543192 & 0.697890 & 0.4942\\
C(24) & -20.04091 & 16.57683 & -1.208971 & 0.2423\\
C(25) & 14.40853 & 11.28733 & 1.276523 & 0.2180\\
C(26) & -0.175476 & 0.326772 & -0.536997 & 0.5978\\
C(27) & 0.381407 & 0.357579 & 1.066639 & 0.3002\\
C(28) & 0.158697 & 0.415639 & 0.381815 & 0.7071\\
C(29) & -1.169850 & 0.545476 & -2.144640 & 0.0459\\
C(30) & 0.600688 & 0.720311 & 0.833929 & 0.4153\\
C(31) & 0.764571 & 0.600755 & 1.272683 & 0.2193\\
C(32) & 1.138401 & 0.514224 & 2.213823 & 0.0400\\
C(33) & -0.139137 & 0.951653 & -0.146206 & 0.8854\\
C(34) & 10.13866 & 21.66531 & 0.467967 & 0.6454\\
\bottomrule
\end{tabular}
\bigskip
\begin{tabular}{lS[table-format=1.5]
lS[table-format=3.3,round-precision=3]}
\multicolumn{4}{l}{Determinant residual covariance: 19.24770}\\
\addlinespace
\multicolumn{4}{l}{\bfseries UNT Observations: 26}\\
R-squared & 0.880742 & Mean dependent var & 4.645045\\
Adjusted R-squared & 0.668727 & S.D. dependent var & 3.567955\\
S.E. of regression & 2.053583 & Sum squared resid & 37.95483\\
Durbin-Watson stat & 1.507160\\
\addlinespace
\multicolumn{4}{l}{\bfseries INF Observations: 26}\\
R-squared & 0.839385 & Mean dependent var & 1.873077\\
Adjusted R-squared & 0.553847 & S.D. dependent var & 9.537570\\
S.E. of regression & 6.370588 & Sum squared resid & 365.2596\\
Durbin-Watson stat & 2.092647\\
\end{tabular}
\end{table}
\end{document}
答案2
一点也不漂亮。
\documentclass{article}
\usepackage{booktabs}
\begin{document}
\centering
\begin{table}
\tiny
\renewcommand{\arraystretch}{1.2}
System:INFLATION AND UNEMPLOYMENT Estimation\par Method: Least Squares\par Sample: 1989 2014\par
Included observations: 26 \medbreak
\begin{tabular}{llllcl}
Total system (balanced) observations 52\\ \toprule & Coefficient & Std. Error & t-Statistic & Prob.\\ \midrule
C(1) & 0.262395 & 0.364940 & 0.719009 & 0.4814\\
C(2) & -0.595551 & 0.622512 & -0.956690 & 0.3514\\
C(3) & 0.279303 & 0.515167 & 0.542160 & 0.5944\\
C(4) & 0.093994 & 0.621750 & 0.151177 & 0.8815\\
C(5) & -0.442089 & 0.436318 & -1.013228 & 0.3244\\
C(6) & 1.575771 & 2.109222 & 0.747086 & 0.4647\\
C(7) & -4.662746 & 5.343604 & -0.872585 & 0.3944\\
C(8) & 2.824077 & 3.638512 & 0.776163 & 0.4477\\
C(9) & 0.176143 & 0.105336 & 1.672193 & 0.1118\\
C(10) & 0.157414 & 0.115267 & 1.365650 & 0.1889\\
C(11) & 0.325583 & 0.133983 & 2.430036 & 0.0258\\
C(12) & -0.044040 &0.175836 & -0.250462 & 0.8051\\
C(13) & 0.290630 & 0.232195 & 1.251663 & 0.2267\\
C(14) & 0.008564 & 0.193656 & 0.044225 & 0.9652\\
C(15) & 0.387795 & 0.165762 &2.339464 & 0.0310\\
C(16) & 0.243521 & 0.306769 & 0.793826 & 0.4376\\
C(17) & 4.818044 & 6.983893 & 0.689879 & 0.4991\\
C(18) & 1.064356 & 1.132110 & 0.940152 & 0.3596\\
C(19) & -1.150959 & 1.931147 & -0.595998 & 0.5586\\
C(20) & 0.654313 & 1.598142 & 0.409421 & 0.6871\\
C(21) & -0.595249 & 1.928781 & -0.308614 & 0.7612\\
C(22) & -1.357195 & 1.353537 & -1.002702 & 0.3293\\
C(23) & 4.566426 & 6.543192 & 0.697890 & 0.4942\\
C(24) & -20.04091 & 16.57683 & -1.208971 & 0.2423\\
C(25) & 14.40853 & 11.28733 & 1.276523 & 0.2180\\
C(26) & -0.175476 & 0.326772 & -0.536997 & 0.5978\\
C(27) & 0.381407 & 0.357579 & 1.066639 & 0.3002\\
C(28) & 0.158697 & 0.415639 & 0.381815 & 0.7071\\
C(29) & -1.169850 & 0.545476 & -2.144640 & 0.0459\\
C(30) & 0.600688 & 0.720311 & 0.833929 & 0.4153\\
C(31) & 0.764571 & 0.600755 & 1.272683 & 0.2193\\
C(32) & 1.138401 & 0.514224 & 2.213823 & 0.0400\\
C(33) & -0.139137 & 0.951653 & -0.146206 & 0.8854\\
C(34) & 10.13866 & 21.66531 & 0.467967 & 0.6454\\ \midrule
Determinant residual covariance & 19.24770\\ \midrule
\bfseries UNT
Observations: 26\\
R-squared & 0.880742 & Mean dependent var & 4.645045\\
Adjusted R-squared & 0.668727 & S.D. dependent var & 3.567955\\
S.E. of regression & 2.053583 & Sum squared resid & 37.95483\\
Durbin-Watson stat & 1.507160\\ \midrule
\bfseries INF
Observations: 26\\
R-squared & 0.839385 & Mean dependent var & 1.873077\\
Adjusted R-squared & 0.553847 & S.D. dependent var & 9.537570\\
S.E. of regression & 6.370588 & Sum squared resid & 365.2596\\
Durbin-Watson stat & 2.092647\\ \bottomrule
\end{tabular}
\end{table}
\end{document}
答案3
它可以放在一页上，\footnotesize看起来更漂亮一些，删除\arraystretch并玩\rlap和\makecell：
\documentclass{article}
\usepackage[showframe]{geometry}
\usepackage{booktabs, makecell}
\usepackage{siunitx}
\centering\sisetup{table-number-alignment = center}
\usepackage{eqparbox}
\begin{document}
\begin{table}
\footnotesize\centering
% \renewcommand{\arraystretch}{1.1} \medbreak
\begin{tabular}{lS[table-format=-2.6]S[table-format=2.6]S[table-format=3.6]S[table-format=1.4]}
\rlap{\makecell[l]{System: INFLATION AND UNEMPLOYMENT Estimation\\
Method: Least Squares\\
Sample: 1989 2014\\
included observations: 26}}\\
\addlinespace
\rlap{\bfseries Total system (balanced) observations 52}\\
\midrule[\heavyrulewidth]
& {Coefficient} & {Std. Error} & {t-Statistic} & {Prob.}\\
\midrule
C(1) & 0.262395 & 0.364940 & 0.719009 & 0.4814\\
C(2) & -0.595551 & 0.622512 & -0.956690 & 0.3514\\
C(3) & 0.279303 & 0.515167 & 0.542160 & 0.5944\\
C(4) & 0.093994 & 0.621750 & 0.151177 & 0.8815\\
C(5) & -0.442089 & 0.436318 & -1.013228 & 0.3244\\
C(6) & 1.575771 & 2.109222 & 0.747086 & 0.4647\\
C(7) & -4.662746 & 5.343604 & -0.872585 & 0.3944\\
C(8) & 2.824077 & 3.638512 & 0.776163 & 0.4477\\
C(9) & 0.176143 & 0.105336 & 1.672193 & 0.1118\\
C(10) & 0.157414 & 0.115267 & 1.365650 & 0.1889\\
C(11) & 0.325583 & 0.133983 & 2.430036 & 0.0258\\
C(12) & -0.044040 &0.175836 & -0.250462 & 0.8051\\
C(13) & 0.290630 & 0.232195 & 1.251663 & 0.2267\\
C(14) & 0.008564 & 0.193656 & 0.044225 & 0.9652\\
C(15) & 0.387795 & 0.165762 &2.339464 & 0.0310\\
C(16) & 0.243521 & 0.306769 & 0.793826 & 0.4376\\
C(17) & 4.818044 & 6.983893 & 0.689879 & 0.4991\\
C(18) & 1.064356 & 1.132110 & 0.940152 & 0.3596\\
C(19) & -1.150959 & 1.931147 & -0.595998 & 0.5586\\
C(20) & 0.654313 & 1.598142 & 0.409421 & 0.6871\\
C(21) & -0.595249 & 1.928781 & -0.308614 & 0.7612\\
C(22) & -1.357195 & 1.353537 & -1.002702 & 0.3293\\
C(23) & 4.566426 & 6.543192 & 0.697890 & 0.4942\\
C(24) & -20.04091 & 16.57683 & -1.208971 & 0.2423\\
C(25) & 14.40853 & 11.28733 & 1.276523 & 0.2180\\
C(26) & -0.175476 & 0.326772 & -0.536997 & 0.5978\\
C(27) & 0.381407 & 0.357579 & 1.066639 & 0.3002\\
C(28) & 0.158697 & 0.415639 & 0.381815 & 0.7071\\
C(29) & -1.169850 & 0.545476 & -2.144640 & 0.0459\\
C(30) & 0.600688 & 0.720311 & 0.833929 & 0.4153\\
C(31) & 0.764571 & 0.600755 & 1.272683 & 0.2193\\
C(32) & 1.138401 & 0.514224 & 2.213823 & 0.0400\\
C(33) & -0.139137 & 0.951653 & -0.146206 & 0.8854\\
C(34) & 10.13866 & 21.66531 & 0.467967 & 0.6454\\
\midrule
\makecell[l]{ Determinant residual\\ covariance} & 19.24770\\
\midrule
\rlap{\bfseries UNT Observations: 26}\\
\addlinespace[0.5ex]
R-squared & 0.880742 & {\eqmakebox[T][l]{Mean dependent var}} & 4.645045\\
Adjusted R-squared & 0.668727 &{\eqmakebox[T][l]{S.D. dependent var}} & 3.567955\\
S.E. of regression & 2.053583 & {\eqmakebox[T][l]{Sum squared resid}} & 37.95483\\
Durbin-Watson stat & 1.507160\\
\midrule
\rlap{\bfseries INF Observations: 26}\\
\addlinespace[0.5ex]
R-squared & 0.839385 & {\eqmakebox[T][l]{Mean dependent var}} & 1.873077\\
Adjusted R-squared & 0.553847 & {\eqmakebox[T][l]{S.D. dependent var}} & 9.537570\\
S.E. of regression & 6.370588 & {\eqmakebox[T][l]{Sum squared resid}} & 365.2596\\
Durbin-Watson stat & 2.092647\\
\bottomrule
\end{tabular}
\end{table}
\end{document}
