Is density() function counts as probability density function?
1
In my assignment, the instructor asked us to plot a histogram in R, then add the probability distribution function on it. So I used the density() function and did something like this:
Did I do it correctly?
My code is:
df <- read.table("values.txt", header=TRUE, sep="t")
hist(df$first, freq=FALSE, col="lightblue", main="", xlab="", ylab="")
lines(density(df$first))
r plot probability-density
edited Nov 9 at 22:02
hrbrmstr
60k685146
asked Nov 9 at 22:00
J. T.
91
add a comment |
1
In my assignment, the instructor asked us to plot a histogram in R, then add the probability distribution function on it. So I used the density() function and did something like this:
Did I do it correctly?
My code is:
df <- read.table("values.txt", header=TRUE, sep="t")
hist(df$first, freq=FALSE, col="lightblue", main="", xlab="", ylab="")
lines(density(df$first))
r plot probability-density
edited Nov 9 at 22:02
hrbrmstr
60k685146
asked Nov 9 at 22:00
J. T.
91
you have implemented it correctly for base graphics 👍🏼
– hrbrmstr
Nov 9 at 22:05
Note that the term "probability distribution function" can sometimes refer to either the PDF or the CDF
– mickey
Nov 9 at 22:39
@mickey so what I did is acceptable as pdf?
– J. T.
Nov 10 at 11:29
@J.T. Yes. Density() gives you an estimate of the pdf. You can play with some of the parameters in density() and get differently shaped pdfs. So while it may not be the "true" pdf, it's a good enough estimate. My comment was meant to be more nitpicky than needed.
– mickey
Nov 10 at 14:42
add a comment |
1
1
1
In my assignment, the instructor asked us to plot a histogram in R, then add the probability distribution function on it. So I used the density() function and did something like this:
Did I do it correctly?
My code is:
df <- read.table("values.txt", header=TRUE, sep="t")
hist(df$first, freq=FALSE, col="lightblue", main="", xlab="", ylab="")
lines(density(df$first))
r plot probability-density
edited Nov 9 at 22:02
hrbrmstr
60k685146
asked Nov 9 at 22:00
J. T.
91
In my assignment, the instructor asked us to plot a histogram in R, then add the probability distribution function on it. So I used the density() function and did something like this:
Did I do it correctly?
My code is:
df <- read.table("values.txt", header=TRUE, sep="t")
hist(df$first, freq=FALSE, col="lightblue", main="", xlab="", ylab="")
lines(density(df$first))
r plot probability-density
r plot probability-density
edited Nov 9 at 22:02
hrbrmstr
60k685146
asked Nov 9 at 22:00
J. T.
91
edited Nov 9 at 22:02
hrbrmstr
60k685146
asked Nov 9 at 22:00
J. T.
91
edited Nov 9 at 22:02
hrbrmstr
60k685146
edited Nov 9 at 22:02
hrbrmstr
60k685146
edited Nov 9 at 22:02
hrbrmstr
60k685146
60k685146
asked Nov 9 at 22:00
J. T.
91
asked Nov 9 at 22:00
J. T.
91
asked Nov 9 at 22:00
J. T.
91
91
you have implemented it correctly for base graphics 👍🏼
– hrbrmstr
Nov 9 at 22:05
Note that the term "probability distribution function" can sometimes refer to either the PDF or the CDF
– mickey
Nov 9 at 22:39
@mickey so what I did is acceptable as pdf?
– J. T.
Nov 10 at 11:29
@J.T. Yes. Density() gives you an estimate of the pdf. You can play with some of the parameters in density() and get differently shaped pdfs. So while it may not be the "true" pdf, it's a good enough estimate. My comment was meant to be more nitpicky than needed.
– mickey
Nov 10 at 14:42
add a comment |
you have implemented it correctly for base graphics 👍🏼
– hrbrmstr
Nov 9 at 22:05
Note that the term "probability distribution function" can sometimes refer to either the PDF or the CDF
– mickey
Nov 9 at 22:39
@mickey so what I did is acceptable as pdf?
– J. T.
Nov 10 at 11:29
@J.T. Yes. Density() gives you an estimate of the pdf. You can play with some of the parameters in density() and get differently shaped pdfs. So while it may not be the "true" pdf, it's a good enough estimate. My comment was meant to be more nitpicky than needed.
– mickey
Nov 10 at 14:42
you have implemented it correctly for base graphics 👍🏼
– hrbrmstr
Nov 9 at 22:05
you have implemented it correctly for base graphics 👍🏼
– hrbrmstr
Nov 9 at 22:05
Note that the term "probability distribution function" can sometimes refer to either the PDF or the CDF
– mickey
Nov 9 at 22:39
Note that the term "probability distribution function" can sometimes refer to either the PDF or the CDF
– mickey
Nov 9 at 22:39
@mickey so what I did is acceptable as pdf?
– J. T.
Nov 10 at 11:29
@mickey so what I did is acceptable as pdf?
– J. T.
Nov 10 at 11:29
@J.T. Yes. Density() gives you an estimate of the pdf. You can play with some of the parameters in density() and get differently shaped pdfs. So while it may not be the "true" pdf, it's a good enough estimate. My comment was meant to be more nitpicky than needed.
– mickey
Nov 10 at 14:42
@J.T. Yes. Density() gives you an estimate of the pdf. You can play with some of the parameters in density() and get differently shaped pdfs. So while it may not be the "true" pdf, it's a good enough estimate. My comment was meant to be more nitpicky than needed.
– mickey
Nov 10 at 14:42
add a comment |
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you have implemented it correctly for base graphics 👍🏼
– hrbrmstr
Nov 9 at 22:05
Note that the term "probability distribution function" can sometimes refer to either the PDF or the CDF
– mickey
Nov 9 at 22:39
@mickey so what I did is acceptable as pdf?
– J. T.
Nov 10 at 11:29
@J.T. Yes. Density() gives you an estimate of the pdf. You can play with some of the parameters in density() and get differently shaped pdfs. So while it may not be the "true" pdf, it's a good enough estimate. My comment was meant to be more nitpicky than needed.
– mickey
Nov 10 at 14:42