Xin Shi
2009-Jan-08 10:33 UTC
[R] how to plot histogram plot and fitted distributions on the same graph
Dear: I am trying to plot the histogram graph for my observed data. Then plot fitted distribution on the same graph of histogram plot in R. 1. histogram plot y. 2. based on "1", plotting y1 v. x; 3. based on "1", plotting y2 v. x; 4. based on "1", plotting y3 v. x; All of these four plots must be on the same graph. However, I found the difficulty is that the y-axis and x-axis for histogram plot and fitted distribution plot are different. For histogram plot, y presents the frequency and x presents events. For fitted distribution plots, y presents the probability and x presents another variable. However, I found out I need histogram plot rather than barplot. This is major problem of this work. The code I used: par(font=1,font.lab=10,font.axis=6) pts18=barplot(y, ylim=c(0,0.2),xlim=c(2,52),axes=FALSE,border=TRUE,names.arg=x,col="white") axis(2,las=1) lines(spline(pts18,y1,n=300,method="natural"),type="l",lty=1) lines(spline(pts18,y2,n=300,method="natural"),type="l",lty=2) lines(spline(pts18,y3,n=300,method="natural"),type="l",lty=5) The data are: The observed data: y<-c(0.098441926, 0.166430595, 0.121813031, 0.104815864, 0.074362606, 0.075779037, 0.055949008, 0.040368272, 0.03470255, 0.029745042, 0.032577904, 0.02266289, 0.014872521, 0.014872521, 0.010623229, 0.01203966, 0.01203966, 0.008498584, 0.009206799, 0.009915014, 0.006373938, 0.003541076, 0.001416431, 0.001416431, 0.005665722, 0.002124646, 0.000708215, 0.001416431, 0.004249292, 0.002832861, 0.004957507, 0.002124646, 0.000708215, 0, 0.000708215, 0.002124646, 0.001416431, 0.001416431, 0.001416431, 0, 0.000708215) Fitted distribution 1: y1<-c(0.03419162, 0.154201321, 0.129581481, 0.108892454, 0.091506645, 0.07689666, 0.064619311, 0.054302168, 0.045632264, 0.0383466, 0.032224168, 0.027079245, 0.022755763, 0.01912257, 0.016069453, 0.013503798, 0.011347777, 0.009535987, 0.008013468, 0.006734034, 0.005658876, 0.004755378, 0.003996132, 0.003358108, 0.002821952, 0.002371398, 0.00199278, 0.001674612, 0.001407243, 0.001182562, 0.000993753, 0.00083509, 0.00070176, 0.000589716, 0.000495562, 0.00041644, 0.000349951, 0.000294078, 0.000247125, 0.000207669, 0.000174513) Fitted distribution 2: y2<-c(0.078909441, 0.188048499, 0.117871979, 0.089827482, 0.072368317, 0.059928019, 0.050453301, 0.042948906, 0.036851702, 0.031809247, 0.027584779, 0.024010745, 0.020963795, 0.01835029, 0.016097393, 0.014147335, 0.012453559, 0.010978051, 0.009689433, 0.008561564, 0.007572497, 0.006703683, 0.005939358, 0.005266055, 0.004672222, 0.004147912, 0.003684531, 0.003274633, 0.002911751, 0.00259025, 0.002305216, 0.002052353, 0.001827898, 0.001628552, 0.001451415, 0.001293939, 0.001153881, 0.001029262, 0.000918338, 0.000819567, 0.000731589) Fitted distribution 3: y3<-c(0.09844545, 0.174856171, 0.1190666, 0.093021492, 0.075639902, 0.062740817, 0.052668044, 0.044568247, 0.037931599, 0.032423244, 0.027808545, 0.023915327, 0.020612892, 0.01779946, 0.015394205, 0.013331948, 0.011559483, 0.010032949, 0.008715898, 0.007577845, 0.006593146, 0.005740133, 0.005000424, 0.004358371, 0.003800615, 0.003315725, 0.002893892, 0.002526689, 0.002206859, 0.001928146, 0.001685148, 0.001473194, 0.001288243, 0.001126794, 0.00098581, 0.000862657, 0.000755047, 0.000660991, 0.000578759, 0.000506847, 0.000443945) x<- c(0, 1, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 200) Many Thanks! Xin [[alternative HTML version deleted]]
Albyn Jones
2009-Jan-08 17:41 UTC
[R] how to plot histogram plot and fitted distributions on the same graph
You are plotting the histogram in the frequency scale. A quick look
at the doc page for hist() would reveal the freq option:
hist(x,freq=FALSE)
then you can add the densities with lines()
albyn
Quoting Xin Shi <jasonshi510 at hotmail.com>:
> Dear:
>
>
>
> I am trying to plot the histogram graph for my observed data. Then plot
> fitted distribution on the same graph of histogram plot in R.
>
>
>
> 1. histogram plot y.
> 2. based on "1", plotting y1 v. x;
> 3. based on "1", plotting y2 v. x;
> 4. based on "1", plotting y3 v. x;
>
>
>
> All of these four plots must be on the same graph.
>
>
>
> However, I found the difficulty is that the y-axis and x-axis for histogram
> plot and fitted distribution plot are different.
>
>
>
> For histogram plot, y presents the frequency and x presents events.
>
>
>
> For fitted distribution plots, y presents the probability and x presents
> another variable.
>
>
>
> However, I found out I need histogram plot rather than barplot. This is
> major problem of this work.
>
>
>
> The code I used:
>
>
>
> par(font=1,font.lab=10,font.axis=6)
>
> pts18=barplot(y,
>
ylim=c(0,0.2),xlim=c(2,52),axes=FALSE,border=TRUE,names.arg=x,col="white")
>
> axis(2,las=1)
>
>
lines(spline(pts18,y1,n=300,method="natural"),type="l",lty=1)
>
>
lines(spline(pts18,y2,n=300,method="natural"),type="l",lty=2)
>
>
lines(spline(pts18,y3,n=300,method="natural"),type="l",lty=5)
>
>
>
> The data are:
>
>
>
> The observed data:
>
>
>
> y<-c(0.098441926, 0.166430595, 0.121813031, 0.104815864, 0.074362606,
>
> 0.075779037, 0.055949008, 0.040368272, 0.03470255, 0.029745042,
>
> 0.032577904, 0.02266289, 0.014872521, 0.014872521, 0.010623229,
>
> 0.01203966, 0.01203966, 0.008498584, 0.009206799, 0.009915014,
>
> 0.006373938, 0.003541076, 0.001416431, 0.001416431, 0.005665722,
>
> 0.002124646, 0.000708215, 0.001416431, 0.004249292, 0.002832861,
>
> 0.004957507, 0.002124646, 0.000708215, 0, 0.000708215, 0.002124646,
>
> 0.001416431, 0.001416431, 0.001416431, 0, 0.000708215)
>
>
>
> Fitted distribution 1:
>
>
>
> y1<-c(0.03419162, 0.154201321, 0.129581481, 0.108892454, 0.091506645,
>
> 0.07689666, 0.064619311, 0.054302168, 0.045632264, 0.0383466,
>
> 0.032224168, 0.027079245, 0.022755763, 0.01912257, 0.016069453,
>
> 0.013503798, 0.011347777, 0.009535987, 0.008013468, 0.006734034,
>
> 0.005658876, 0.004755378, 0.003996132, 0.003358108, 0.002821952,
>
> 0.002371398, 0.00199278, 0.001674612, 0.001407243, 0.001182562,
>
> 0.000993753, 0.00083509, 0.00070176, 0.000589716, 0.000495562,
>
> 0.00041644, 0.000349951, 0.000294078, 0.000247125, 0.000207669,
>
> 0.000174513)
>
>
>
> Fitted distribution 2:
>
>
>
> y2<-c(0.078909441, 0.188048499, 0.117871979, 0.089827482, 0.072368317,
>
> 0.059928019, 0.050453301, 0.042948906, 0.036851702, 0.031809247,
>
> 0.027584779, 0.024010745, 0.020963795, 0.01835029, 0.016097393,
>
> 0.014147335, 0.012453559, 0.010978051, 0.009689433, 0.008561564,
>
> 0.007572497, 0.006703683, 0.005939358, 0.005266055, 0.004672222,
>
> 0.004147912, 0.003684531, 0.003274633, 0.002911751, 0.00259025,
>
> 0.002305216, 0.002052353, 0.001827898, 0.001628552, 0.001451415,
>
> 0.001293939, 0.001153881, 0.001029262, 0.000918338, 0.000819567,
>
> 0.000731589)
>
>
>
> Fitted distribution 3:
>
>
>
> y3<-c(0.09844545, 0.174856171, 0.1190666, 0.093021492, 0.075639902,
>
> 0.062740817, 0.052668044, 0.044568247, 0.037931599, 0.032423244,
>
> 0.027808545, 0.023915327, 0.020612892, 0.01779946, 0.015394205,
>
> 0.013331948, 0.011559483, 0.010032949, 0.008715898, 0.007577845,
>
> 0.006593146, 0.005740133, 0.005000424, 0.004358371, 0.003800615,
>
> 0.003315725, 0.002893892, 0.002526689, 0.002206859, 0.001928146,
>
> 0.001685148, 0.001473194, 0.001288243, 0.001126794, 0.00098581,
>
> 0.000862657, 0.000755047, 0.000660991, 0.000578759, 0.000506847,
>
> 0.000443945)
>
>
>
> x<- c(0, 1, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55,
>
> 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115,
>
> 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170,
>
> 175, 180, 185, 190, 200)
>
>
>
> Many Thanks!
>
>
>
> Xin
>
>
>
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
>
Greg Snow
2009-Jan-08 19:00 UTC
[R] how to plot histogram plot and fitted distributions on the same graph
Here is a direct quote from the help page for hist: "if 'FALSE', probability densities, component 'density', are plotted (so that the histogram has a total area of one)." That looks like it may apply to your problem, just figure out what the above quote is referring to. The last example on that help page shows a distribution curve over a histogram, and it is not that complicated. There are other gems on knowledge hidden on that page, I recommend reading the whole thing. -- Gregory (Greg) L. Snow Ph.D. Statistical Data Center Intermountain Healthcare greg.snow at imail.org 801.408.8111> -----Original Message----- > From: r-help-bounces at r-project.org [mailto:r-help-bounces at r- > project.org] On Behalf Of Xin Shi > Sent: Thursday, January 08, 2009 3:33 AM > To: r-help at r-project.org > Subject: [R] how to plot histogram plot and fitted distributions on the > same graph > > Dear: > > > > I am trying to plot the histogram graph for my observed data. Then plot > fitted distribution on the same graph of histogram plot in R. > > > > 1. histogram plot y. > 2. based on "1", plotting y1 v. x; > 3. based on "1", plotting y2 v. x; > 4. based on "1", plotting y3 v. x; > > > > All of these four plots must be on the same graph. > > > > However, I found the difficulty is that the y-axis and x-axis for > histogram > plot and fitted distribution plot are different. > > > > For histogram plot, y presents the frequency and x presents events. > > > > For fitted distribution plots, y presents the probability and x > presents > another variable. > > > > However, I found out I need histogram plot rather than barplot. This is > major problem of this work. > > > > The code I used: > > > > par(font=1,font.lab=10,font.axis=6) > > pts18=barplot(y, > ylim=c(0,0.2),xlim=c(2,52),axes=FALSE,border=TRUE,names.arg=x,col="whit > e") > > axis(2,las=1) > > lines(spline(pts18,y1,n=300,method="natural"),type="l",lty=1) > > lines(spline(pts18,y2,n=300,method="natural"),type="l",lty=2) > > lines(spline(pts18,y3,n=300,method="natural"),type="l",lty=5) > > > > The data are: > > > > The observed data: > > > > y<-c(0.098441926, 0.166430595, 0.121813031, 0.104815864, 0.074362606, > > 0.075779037, 0.055949008, 0.040368272, 0.03470255, 0.029745042, > > 0.032577904, 0.02266289, 0.014872521, 0.014872521, 0.010623229, > > 0.01203966, 0.01203966, 0.008498584, 0.009206799, 0.009915014, > > 0.006373938, 0.003541076, 0.001416431, 0.001416431, 0.005665722, > > 0.002124646, 0.000708215, 0.001416431, 0.004249292, 0.002832861, > > 0.004957507, 0.002124646, 0.000708215, 0, 0.000708215, 0.002124646, > > 0.001416431, 0.001416431, 0.001416431, 0, 0.000708215) > > > > Fitted distribution 1: > > > > y1<-c(0.03419162, 0.154201321, 0.129581481, 0.108892454, 0.091506645, > > 0.07689666, 0.064619311, 0.054302168, 0.045632264, 0.0383466, > > 0.032224168, 0.027079245, 0.022755763, 0.01912257, 0.016069453, > > 0.013503798, 0.011347777, 0.009535987, 0.008013468, 0.006734034, > > 0.005658876, 0.004755378, 0.003996132, 0.003358108, 0.002821952, > > 0.002371398, 0.00199278, 0.001674612, 0.001407243, 0.001182562, > > 0.000993753, 0.00083509, 0.00070176, 0.000589716, 0.000495562, > > 0.00041644, 0.000349951, 0.000294078, 0.000247125, 0.000207669, > > 0.000174513) > > > > Fitted distribution 2: > > > > y2<-c(0.078909441, 0.188048499, 0.117871979, 0.089827482, 0.072368317, > > 0.059928019, 0.050453301, 0.042948906, 0.036851702, 0.031809247, > > 0.027584779, 0.024010745, 0.020963795, 0.01835029, 0.016097393, > > 0.014147335, 0.012453559, 0.010978051, 0.009689433, 0.008561564, > > 0.007572497, 0.006703683, 0.005939358, 0.005266055, 0.004672222, > > 0.004147912, 0.003684531, 0.003274633, 0.002911751, 0.00259025, > > 0.002305216, 0.002052353, 0.001827898, 0.001628552, 0.001451415, > > 0.001293939, 0.001153881, 0.001029262, 0.000918338, 0.000819567, > > 0.000731589) > > > > Fitted distribution 3: > > > > y3<-c(0.09844545, 0.174856171, 0.1190666, 0.093021492, 0.075639902, > > 0.062740817, 0.052668044, 0.044568247, 0.037931599, 0.032423244, > > 0.027808545, 0.023915327, 0.020612892, 0.01779946, 0.015394205, > > 0.013331948, 0.011559483, 0.010032949, 0.008715898, 0.007577845, > > 0.006593146, 0.005740133, 0.005000424, 0.004358371, 0.003800615, > > 0.003315725, 0.002893892, 0.002526689, 0.002206859, 0.001928146, > > 0.001685148, 0.001473194, 0.001288243, 0.001126794, 0.00098581, > > 0.000862657, 0.000755047, 0.000660991, 0.000578759, 0.000506847, > > 0.000443945) > > > > x<- c(0, 1, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, > > 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, > > 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, > > 175, 180, 185, 190, 200) > > > > Many Thanks! > > > > Xin > > > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting- > guide.html > and provide commented, minimal, self-contained, reproducible code.