Plotting mathematical functions with curve

Simple mathematical functions can be plotted quickly with curve() to show their shape. Multiple curves can be overlain by including "add = TRUE" in the call to subsequent curves.


Example 1:
#Negative exponential, a common survival function
curve(exp(-0.5*x),xlim = c(0,10) , ylim = c(0,2), col = 4, lwd = 6, lty = 4)

#Ricker model, use in fisheries modeling
curve(2*x*exp(-0.5*x), add = TRUE, col = 2, lwd = 5, lty = 3)

#A legend with the appropriate colors, line types. "cex" increases the font size.
legend("topright", c("Neg exponential", "Ricker"), lty=c(4,3),col=c(4,2), bty="n", lwd = 5, cex =2)


Example 2:
#The logistic function
curve( exp(1*+ 1*x) / ( 1 + exp(1 + 1*x) ), xlim = c(-10,10) , ylim = c(0,2))

#Overlaying a Gompertz function
curve(1*exp(-1*exp(-2*x)), add = TRUE)

Overlaying two histograms with "add=TRUE"

#Two histograms can be overlain by putting the command "add = TRUE" in the call for the second histogram.

#Make sure that the height of the y-axis can accommodate both sets of data - the y axis appears to be set by the first hist() command.

#Colors for the two graphs can be set using col="red"

par(mfrow=c(1,1)) #this tells R to graph 1 plot at a time

#The first histogram. xlim= and ylim= set the axes, and main= and xlab= the labels
hist( subset(practice_S$L_2003, practice_S$s_2003=="Y"), col="red",xlim=c(0,125), ylim = c(0, 125), xlab="length (mm)", main="L_2003 - flwring")

#The second histogram, with the "add=TRUE" commend
hist( subset(practice_S$L_2003, practice_S$s_2003=="N"), col="green",add=TRUE ,xlim=c(0,125), xlab="length (mm)", main="L_2003 - non-flwring")

#One problem with this approach is bars that occur directly on top of each other get obscured. An alternative is to plot each set of data as a density function, or to just plot them side by side.




#If I wanted to plot these histograms like this, I could change the par() statement to (1,2) and remove the "add=TRUE" statement in the second histogram

par(mfrow=c(1,2))

#The first histogram
hist( subset(practice_S$L_2003, practice_S$s_2003=="Y"), col="red",xlim=c(0,100), ylim = c(0, 125), xlab="length (mm)", main="L_2003 - flwring")

#The second histogram,
hist( subset(practice_S$L_2003, practice_S$s_2003=="N"), col="green",xlim=c(0,100), xlab="length (mm)", main="L_2003 - non-flwring")

Plotting vectors using segments()

#A classmate needed to plot some vectors for a power point presentation. Here's some basic #code for plotting lines in R:

#First, tell R you want to make a plot. I'll make two objects that just contain zeros and tell R to #plot them, which is just a quick way to get the plotting process started.

x<-0 y<-0 plot(x,y, type="l", xlim=c(-1,1), ylim=c(-1,1))

#type="l" tells it to plot x and y as a line - since its just the point (0,0) you get nothing.
#xlim=c() and ylim=c() sets the axes
#You can plot lines using segments()

segments(x0=0, y0=0, x1=0, y1=-1, col=2)
segments(x0=0, y0=0, x1=-0.5, y1=-0.5, col=3)

#col=2 gives you read, while col=3 is green

#You can plot arrows with arrows()

arrows(x0=0, y0=0, x1=0, y1=1, col=2) arrows(x0=0, y0=0, x1=0.5, y1=0.5, col=3)

#A quick way to plot lines is abline(). This is often used to plot lines on graphs of statistical #models. (0,0) tells abline to plot a line at with a y intercept of zer and a slope of 0. (1,1) would #make a 45 degree line.

abline(0,0, lty="dashed")

#lty= means "line type"

#for more info on adjusting graphs, lines, and axes, see

help(plot.default)

#and

help(par)