visreg: overlay two models in a single plot
I'm trying to draw in a single plot crude and adjusted GAM models using library visreg
:
# Create DF
set.seed(123)
x1 = rnorm(2000)
z = 1 + 3*x1 + 3*exp(x1)
pr = 1/(1+exp(-z))
y = rbinom(2000,1,pr)
df = data.frame(y=y,x1=x1, x2=exp(x1)*z)
# Fitting GAMs
library(mgcv)
crude <- gam(y ~ s(x1), family=binomial(link=logit), data=df)
adj <- gam(y ~ s(x1) + s(x2), family=binomial(link=logit), data=df)
# Plot results using 'visreg'
library(visreg)
p.crude <- visreg(crude, scale='response', "x1", line.par = list(col = 'red'), gg=TRUE) + theme_bw()
p.adj <- visreg(adj, scale='response', "x1", gg=TRUE) + theme_bw()
Using gridExtra
I can produce a two columns plot, however I would have a single plot which overlays the two model plots.
r ggplot2 gridextra
add a comment |
I'm trying to draw in a single plot crude and adjusted GAM models using library visreg
:
# Create DF
set.seed(123)
x1 = rnorm(2000)
z = 1 + 3*x1 + 3*exp(x1)
pr = 1/(1+exp(-z))
y = rbinom(2000,1,pr)
df = data.frame(y=y,x1=x1, x2=exp(x1)*z)
# Fitting GAMs
library(mgcv)
crude <- gam(y ~ s(x1), family=binomial(link=logit), data=df)
adj <- gam(y ~ s(x1) + s(x2), family=binomial(link=logit), data=df)
# Plot results using 'visreg'
library(visreg)
p.crude <- visreg(crude, scale='response', "x1", line.par = list(col = 'red'), gg=TRUE) + theme_bw()
p.adj <- visreg(adj, scale='response', "x1", gg=TRUE) + theme_bw()
Using gridExtra
I can produce a two columns plot, however I would have a single plot which overlays the two model plots.
r ggplot2 gridextra
add a comment |
I'm trying to draw in a single plot crude and adjusted GAM models using library visreg
:
# Create DF
set.seed(123)
x1 = rnorm(2000)
z = 1 + 3*x1 + 3*exp(x1)
pr = 1/(1+exp(-z))
y = rbinom(2000,1,pr)
df = data.frame(y=y,x1=x1, x2=exp(x1)*z)
# Fitting GAMs
library(mgcv)
crude <- gam(y ~ s(x1), family=binomial(link=logit), data=df)
adj <- gam(y ~ s(x1) + s(x2), family=binomial(link=logit), data=df)
# Plot results using 'visreg'
library(visreg)
p.crude <- visreg(crude, scale='response', "x1", line.par = list(col = 'red'), gg=TRUE) + theme_bw()
p.adj <- visreg(adj, scale='response', "x1", gg=TRUE) + theme_bw()
Using gridExtra
I can produce a two columns plot, however I would have a single plot which overlays the two model plots.
r ggplot2 gridextra
I'm trying to draw in a single plot crude and adjusted GAM models using library visreg
:
# Create DF
set.seed(123)
x1 = rnorm(2000)
z = 1 + 3*x1 + 3*exp(x1)
pr = 1/(1+exp(-z))
y = rbinom(2000,1,pr)
df = data.frame(y=y,x1=x1, x2=exp(x1)*z)
# Fitting GAMs
library(mgcv)
crude <- gam(y ~ s(x1), family=binomial(link=logit), data=df)
adj <- gam(y ~ s(x1) + s(x2), family=binomial(link=logit), data=df)
# Plot results using 'visreg'
library(visreg)
p.crude <- visreg(crude, scale='response', "x1", line.par = list(col = 'red'), gg=TRUE) + theme_bw()
p.adj <- visreg(adj, scale='response', "x1", gg=TRUE) + theme_bw()
Using gridExtra
I can produce a two columns plot, however I would have a single plot which overlays the two model plots.
r ggplot2 gridextra
r ggplot2 gridextra
asked Nov 11 at 15:44
Borexino
969
969
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1 Answer
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You can use the plot=FALSE
parameter to get the data without the plots:
p.crude <- visreg(crude, scale='response', "x1", line.par = list(col = 'red'), plot=FALSE)
p.adj <- visreg(adj, scale='response', "x1", plot = FALSE)
And, then re-create it by hand:
dplyr::bind_rows(
dplyt::mutate(p.crude$fit, plt = "crude"),
dplyr::mutate(p.adj$fit, plt = "adj")
) -> fits
ggplot() +
geom_ribbon(
data = fits,
aes(x1, ymin=visregLwr, ymax=visregUpr, group=plt), fill="gray90"
) +
geom_line(data = fits, aes(x1, visregFit, group=plt, color=plt)) +
theme_bw()
https://github.com/pbreheny/visreg/blob/master/R/ggFactorPlot.R has all the other computations and geoms/aesthetics you can use in the recreation.
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
You can use the plot=FALSE
parameter to get the data without the plots:
p.crude <- visreg(crude, scale='response', "x1", line.par = list(col = 'red'), plot=FALSE)
p.adj <- visreg(adj, scale='response', "x1", plot = FALSE)
And, then re-create it by hand:
dplyr::bind_rows(
dplyt::mutate(p.crude$fit, plt = "crude"),
dplyr::mutate(p.adj$fit, plt = "adj")
) -> fits
ggplot() +
geom_ribbon(
data = fits,
aes(x1, ymin=visregLwr, ymax=visregUpr, group=plt), fill="gray90"
) +
geom_line(data = fits, aes(x1, visregFit, group=plt, color=plt)) +
theme_bw()
https://github.com/pbreheny/visreg/blob/master/R/ggFactorPlot.R has all the other computations and geoms/aesthetics you can use in the recreation.
add a comment |
You can use the plot=FALSE
parameter to get the data without the plots:
p.crude <- visreg(crude, scale='response', "x1", line.par = list(col = 'red'), plot=FALSE)
p.adj <- visreg(adj, scale='response', "x1", plot = FALSE)
And, then re-create it by hand:
dplyr::bind_rows(
dplyt::mutate(p.crude$fit, plt = "crude"),
dplyr::mutate(p.adj$fit, plt = "adj")
) -> fits
ggplot() +
geom_ribbon(
data = fits,
aes(x1, ymin=visregLwr, ymax=visregUpr, group=plt), fill="gray90"
) +
geom_line(data = fits, aes(x1, visregFit, group=plt, color=plt)) +
theme_bw()
https://github.com/pbreheny/visreg/blob/master/R/ggFactorPlot.R has all the other computations and geoms/aesthetics you can use in the recreation.
add a comment |
You can use the plot=FALSE
parameter to get the data without the plots:
p.crude <- visreg(crude, scale='response', "x1", line.par = list(col = 'red'), plot=FALSE)
p.adj <- visreg(adj, scale='response', "x1", plot = FALSE)
And, then re-create it by hand:
dplyr::bind_rows(
dplyt::mutate(p.crude$fit, plt = "crude"),
dplyr::mutate(p.adj$fit, plt = "adj")
) -> fits
ggplot() +
geom_ribbon(
data = fits,
aes(x1, ymin=visregLwr, ymax=visregUpr, group=plt), fill="gray90"
) +
geom_line(data = fits, aes(x1, visregFit, group=plt, color=plt)) +
theme_bw()
https://github.com/pbreheny/visreg/blob/master/R/ggFactorPlot.R has all the other computations and geoms/aesthetics you can use in the recreation.
You can use the plot=FALSE
parameter to get the data without the plots:
p.crude <- visreg(crude, scale='response', "x1", line.par = list(col = 'red'), plot=FALSE)
p.adj <- visreg(adj, scale='response', "x1", plot = FALSE)
And, then re-create it by hand:
dplyr::bind_rows(
dplyt::mutate(p.crude$fit, plt = "crude"),
dplyr::mutate(p.adj$fit, plt = "adj")
) -> fits
ggplot() +
geom_ribbon(
data = fits,
aes(x1, ymin=visregLwr, ymax=visregUpr, group=plt), fill="gray90"
) +
geom_line(data = fits, aes(x1, visregFit, group=plt, color=plt)) +
theme_bw()
https://github.com/pbreheny/visreg/blob/master/R/ggFactorPlot.R has all the other computations and geoms/aesthetics you can use in the recreation.
answered Nov 11 at 16:02
hrbrmstr
60k685146
60k685146
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