Repeat is a construct that basically intiali, initiates and infinite loop.

This is not a what I would characterize as a commonly used control structure in R but

it does have its use occasionally.

So the only way to exit a repeat loop is to call break, so

obviously you are going to have to call break at some point,

unless you feel like running your program, you know, forever.

So here is a pretty simple example, here I am initializing a value of x 0 to be 1,

and I am saying what I think of as a tolerance to be 10 to the minus 8, and

then I am going to repeat the following structure.

Basically, I'm going to, I imagine that some function that keep

computing estimate for x and I'm going to call that x1.

And basically if, if the new value of x that is x1,

is, is, if the absolute value of the difference between x1 and

x0 is less than some tolerance, in this case 10 to the minus 8,

then I'm going to stop the loop and then move on to the next bit of code.

If, if the, if the difference is greater than my tolerance,

then I set x0 to be equal to the new value.

And then I, I run the loop again, I calculate a new estimate and

I check to see if, if the difference is small.

So, this is a common type of formulation in in many types of

optimization algorithms, for

example, if you're trying to find the solution to some set of equations, or

you're trying to maximize the function, often you'll iterate over and over again.

And and you'll stop when the,

when the estimates that you're calculating are getting closer and

closer together, because that's usually a sign that you're kind of converging to

whatever the minimum or ma, or maximum of the objective function is.

So this is a, in theory this is a perfectly reasonable construction.

You want to keep recycling through the algorithm until the two values are close.

So there's one problem which is that first of all requires an algorithm that is

guaranteed to converge and not necessarily every algorithm has that property.

Second of all, als, it doe, it, it does depend a little bit on the tolerance of

the re, the loop will run longer if the tolerance is smaller, generally speaking.

And because it's hard to predict how how long this loop will run.

It can be a little bit dangerous because it's a little bit

because it's unpredictable, it, it, it could theoretically run forever, and

you have no gar, way to guarantee that the program will stop at some point.

So this construct,

although it's theoretically kind of the right thing to do

it's usually not a good idea.

It's better, probably be better off to use a for loop that has a,

has a hard limit on the number of iterations that it's allowed to run.

That way, if you have a problem with your algorithm, it will eventually reach

the hard limit and stop and, and you will know that the reason it stopped is because

it didn't converge and then maybe you can try to fix something about the algorithm.

But with a repeat type of approach if your algorithm is not converging you won't

have any warning it will just be running a really long time.