I am using widetext.sty to span the equations over two columns. The output which is coming is perfect
I would like to add linenumbers using lineno.sty, if I do so, the linenumbers is merging with the inner margin (see below screenshot).
Could anyone guide me how to resolve this issue?
My code is:
\documentclass[twocolumn]{article}
\usepackage{amsmath,multicol}
\usepackage[switch,right]{lineno}
\linenumbers
\usepackage{widetext}
\begin{document}
Line 1 In practice, we often have little prior information
implying that the models for regressing the response
variable on the covariates are linear or any other
parametric family. Compared with a parametric model, more
flexibility is possible by using a nonparametric model,
such as the additive model.
Line 2 In practice, we often have little prior information
implying that the models for regressing the response
variable on the covariates are linear or any other
parametric family. Compared with a parametric model, more
flexibility is possible by using a nonparametric model,
such as the additive model.
Line 3 In practice, we often have little prior information
implying that the models for regressing the response
variable on the covariates are linear or any other
parametric family. Compared with a parametric model, more
flexibility is possible by using a nonparametric model,
such as the additive model.\par
\begin{widetext}
\begin{equation}
\mathcal{R}^{(\text{d})}=
g_{\sigma_2}^e
\left(
\frac{[\Gamma^Z(3,21)]_{\sigma_1}}{Q_{12}^2-M_W^2}
+\frac{[\Gamma^Z(13,2)]_{\sigma_1}}{Q_{13}^2-M_W^2}
\right)
+ x_WQ_e
\left(
\frac{[\Gamma^\gamma(3,21)]_{\sigma_1}}{Q_{12}^2-M_W^2}
+\frac{[\Gamma^\gamma(13,2)]_{\sigma_1}}{Q_{13}^2-M_W^2}
\right)\;. \label{eq:wideeq}
\end{equation}
\end{widetext}
Line 4 In practice, we often have little prior information
implying that the models for regressing the response
variable on the covariates are linear or any other
parametric family. Compared with a parametric model, more
flexibility is possible by using a nonparametric model,
such as the additive model.
Line 5 In practice, we often have little prior information
implying that the models for regressing the response
variable on the covariates are linear or any other
parametric family. Compared with a parametric model, more
flexibility is possible by using a nonparametric model,
such as the additive model.
Line 6 In practice, we often have little prior information
implying that the models for regressing the response
variable on the covariates are linear or any other
parametric family. Compared with a parametric model, more
flexibility is possible by using a nonparametric model,
such as the additive model.
Line 7 In practice, we often have little prior information
implying that the models for regressing the response
variable on the covariates are linear or any other
parametric family. Compared with a parametric model, more
flexibility is possible by using a nonparametric model,
such as the additive model.
Line 8 In practice, we often have little prior information
implying that the models for regressing the response
variable on the covariates are linear or any other
parametric family. Compared with a parametric model, more
flexibility is possible by using a nonparametric model,
such as the additive model.
Line 9 In practice, we often have little prior information
implying that the models for regressing the response
variable on the covariates are linear or any other
parametric family. Compared with a parametric model, more
flexibility is possible by using a nonparametric model,
such as the additive model.
Line 10 In practice, we often have little prior information
implying that the models for regressing the response
variable on the covariates are linear or any other
parametric family. Compared with a parametric model, more
flexibility is possible by using a nonparametric model,
such as the additive model.
Line 11 In practice, we often have little prior information
implying that the models for regressing the response
variable on the covariates are linear or any other
parametric family. Compared with a parametric model, more
flexibility is possible by using a nonparametric model,
such as the additive model.
\clearpage
\end{document}
Thanks
S. Vinayagamurthy
