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Plot shifted t-distribution with ggplot2
Rotating and spacing axis labels in ggplot2What do hjust and vjust do when making a plot using ggplot?Overlaying a normal distribution on a histogramPlot quantiles of distribution in ggplot2 with facetsIs there any “add” parameter (like in graphics::curve) for ggplot2?Illustrate mean and standard deviation in ggplot2 density plotHow to plot a set of rotated densities in ggplot2?Trying to add normal distribution curve to ggplot, and it's not workingggplot - altering the height of each overlapping variable on a density plotHow to plot two distribution curves in a faceted way in R / ggplot2?
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I am trying to plot the density curve of a t-distribution with mean = 3 and df = 1.5 using ggplot2. However it is supposed to be symmetric around 3, so I can not use the noncentrality parameter.
ggplot(data.frame(x = c(-4, 10)), aes(x = x)) +
stat_function(fun = dt, args = list(df = 1.5))
Is there a way to simply shift the distribution along the x-axis?
r ggplot2
asked Feb 3 '17 at 14:23
nhoeftnhoeft
15012
add a comment |
I am trying to plot the density curve of a t-distribution with mean = 3 and df = 1.5 using ggplot2. However it is supposed to be symmetric around 3, so I can not use the noncentrality parameter.
ggplot(data.frame(x = c(-4, 10)), aes(x = x)) +
stat_function(fun = dt, args = list(df = 1.5))
Is there a way to simply shift the distribution along the x-axis?
r ggplot2
asked Feb 3 '17 at 14:23
nhoeftnhoeft
15012
add a comment |
I am trying to plot the density curve of a t-distribution with mean = 3 and df = 1.5 using ggplot2. However it is supposed to be symmetric around 3, so I can not use the noncentrality parameter.
ggplot(data.frame(x = c(-4, 10)), aes(x = x)) +
stat_function(fun = dt, args = list(df = 1.5))
Is there a way to simply shift the distribution along the x-axis?
r ggplot2
asked Feb 3 '17 at 14:23
nhoeftnhoeft
15012
I am trying to plot the density curve of a t-distribution with mean = 3 and df = 1.5 using ggplot2. However it is supposed to be symmetric around 3, so I can not use the noncentrality parameter.
ggplot(data.frame(x = c(-4, 10)), aes(x = x)) +
stat_function(fun = dt, args = list(df = 1.5))
Is there a way to simply shift the distribution along the x-axis?
r ggplot2
r ggplot2
asked Feb 3 '17 at 14:23
nhoeftnhoeft
15012
asked Feb 3 '17 at 14:23
nhoeftnhoeft
15012
asked Feb 3 '17 at 14:23
nhoeftnhoeft
15012
asked Feb 3 '17 at 14:23
nhoeftnhoeft
15012
asked Feb 3 '17 at 14:23
nhoeftnhoeft
15012
15012
add a comment |
add a comment |
3 Answers
3
active
oldest
votes
you could also make a custom function for your shifted t-distribution:
custom <- function(x) dt(x - 3, 1.5)
ggplot(data.frame(x = c(-4, 10)), aes(x = x)) +
stat_function(fun = custom)
answered Feb 3 '17 at 14:42
NateNate
6,71512030
add a comment |
A simple solution is to just change the labels instead:
ggplot(data.frame(x = c(-4, 10)), aes(x = x)) +
stat_function(fun = dt, args = list(df = 1.5)) +
scale_x_continuous(breaks = c(0, 5, 10), labels = c(3, 8, 13))
answered Feb 3 '17 at 14:35
AxemanAxeman
19.3k54559
add a comment |
There is also a function dt.scaled in the metRology package, which in addition to the df, lets you specify the mean and scale.
Relevant code:
dt.scaled <- function(x, df, mean = 0, sd = 1, ncp, log = FALSE)
if (!log) stats::dt((x - mean)/sd, df, ncp = ncp, log = FALSE)/sd
else stats::dt((x - mean)/sd, df, ncp = ncp, log = TRUE) - log(sd)
answered Mar 9 at 3:37
kwiebelskwiebels
1
add a comment |
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3 Answers
3
active
oldest
votes
3 Answers
3
active
oldest
votes
active
oldest
votes
active
oldest
votes
you could also make a custom function for your shifted t-distribution:
custom <- function(x) dt(x - 3, 1.5)
ggplot(data.frame(x = c(-4, 10)), aes(x = x)) +
stat_function(fun = custom)
answered Feb 3 '17 at 14:42
NateNate
6,71512030
add a comment |
you could also make a custom function for your shifted t-distribution:
custom <- function(x) dt(x - 3, 1.5)
ggplot(data.frame(x = c(-4, 10)), aes(x = x)) +
stat_function(fun = custom)
answered Feb 3 '17 at 14:42
NateNate
6,71512030
add a comment |
you could also make a custom function for your shifted t-distribution:
custom <- function(x) dt(x - 3, 1.5)
ggplot(data.frame(x = c(-4, 10)), aes(x = x)) +
stat_function(fun = custom)
answered Feb 3 '17 at 14:42
NateNate
6,71512030
you could also make a custom function for your shifted t-distribution:
custom <- function(x) dt(x - 3, 1.5)
ggplot(data.frame(x = c(-4, 10)), aes(x = x)) +
stat_function(fun = custom)
answered Feb 3 '17 at 14:42
NateNate
6,71512030
answered Feb 3 '17 at 14:42
NateNate
6,71512030
answered Feb 3 '17 at 14:42
NateNate
6,71512030
answered Feb 3 '17 at 14:42
NateNate
6,71512030
6,71512030
add a comment |
add a comment |
A simple solution is to just change the labels instead:
ggplot(data.frame(x = c(-4, 10)), aes(x = x)) +
stat_function(fun = dt, args = list(df = 1.5)) +
scale_x_continuous(breaks = c(0, 5, 10), labels = c(3, 8, 13))
answered Feb 3 '17 at 14:35
AxemanAxeman
19.3k54559
add a comment |
A simple solution is to just change the labels instead:
ggplot(data.frame(x = c(-4, 10)), aes(x = x)) +
stat_function(fun = dt, args = list(df = 1.5)) +
scale_x_continuous(breaks = c(0, 5, 10), labels = c(3, 8, 13))
answered Feb 3 '17 at 14:35
AxemanAxeman
19.3k54559
add a comment |
A simple solution is to just change the labels instead:
ggplot(data.frame(x = c(-4, 10)), aes(x = x)) +
stat_function(fun = dt, args = list(df = 1.5)) +
scale_x_continuous(breaks = c(0, 5, 10), labels = c(3, 8, 13))
answered Feb 3 '17 at 14:35
AxemanAxeman
19.3k54559
A simple solution is to just change the labels instead:
ggplot(data.frame(x = c(-4, 10)), aes(x = x)) +
stat_function(fun = dt, args = list(df = 1.5)) +
scale_x_continuous(breaks = c(0, 5, 10), labels = c(3, 8, 13))
answered Feb 3 '17 at 14:35
AxemanAxeman
19.3k54559
answered Feb 3 '17 at 14:35
AxemanAxeman
19.3k54559
answered Feb 3 '17 at 14:35
AxemanAxeman
19.3k54559
answered Feb 3 '17 at 14:35
AxemanAxeman
19.3k54559
19.3k54559
add a comment |
add a comment |
There is also a function dt.scaled in the metRology package, which in addition to the df, lets you specify the mean and scale.
Relevant code:
dt.scaled <- function(x, df, mean = 0, sd = 1, ncp, log = FALSE)
if (!log) stats::dt((x - mean)/sd, df, ncp = ncp, log = FALSE)/sd
else stats::dt((x - mean)/sd, df, ncp = ncp, log = TRUE) - log(sd)
answered Mar 9 at 3:37
kwiebelskwiebels
1
add a comment |
There is also a function dt.scaled in the metRology package, which in addition to the df, lets you specify the mean and scale.
Relevant code:
dt.scaled <- function(x, df, mean = 0, sd = 1, ncp, log = FALSE)
if (!log) stats::dt((x - mean)/sd, df, ncp = ncp, log = FALSE)/sd
else stats::dt((x - mean)/sd, df, ncp = ncp, log = TRUE) - log(sd)
answered Mar 9 at 3:37
kwiebelskwiebels
1
add a comment |
There is also a function dt.scaled in the metRology package, which in addition to the df, lets you specify the mean and scale.
Relevant code:
dt.scaled <- function(x, df, mean = 0, sd = 1, ncp, log = FALSE)
if (!log) stats::dt((x - mean)/sd, df, ncp = ncp, log = FALSE)/sd
else stats::dt((x - mean)/sd, df, ncp = ncp, log = TRUE) - log(sd)
answered Mar 9 at 3:37
kwiebelskwiebels
1
There is also a function dt.scaled in the metRology package, which in addition to the df, lets you specify the mean and scale.
Relevant code:
dt.scaled <- function(x, df, mean = 0, sd = 1, ncp, log = FALSE)
if (!log) stats::dt((x - mean)/sd, df, ncp = ncp, log = FALSE)/sd
else stats::dt((x - mean)/sd, df, ncp = ncp, log = TRUE) - log(sd)
answered Mar 9 at 3:37
kwiebelskwiebels
1
answered Mar 9 at 3:37
kwiebelskwiebels
1
answered Mar 9 at 3:37
kwiebelskwiebels
1
answered Mar 9 at 3:37
kwiebelskwiebels
1
1
add a comment |
add a comment |
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