How can we know beforehand at what f looks like and what p should be?

saphirasnow

Do we start with a complete understanding of f and p?

spidey

How do we figure out what p should be if we don't know exactly what f looks like when sampling?

mangopi

Is there a way to do this dynamically, i.e. if our function is just an input stream of data points?

snaminen

How did we derive the graphs of f and p?

YutianW

Is there a specific way that we can know p if we do not know what exactly is f like?

coolpotato

I am still a little confused. Where does this probability distribution p come from? Does it depend on the function f or the material of the object?

David

I am confused with why this works. If you can have a good estimate of p(x), doesn't this also mean that you have an estimate of f(x) and you can just solve for the integral?

Bellala

How do we get f and p specifically?

Mogician

After we switch our sample distribution, the biasness has not changed right? What about consistency?

How can we know beforehand at what f looks like and what p should be?

Do we start with a complete understanding of f and p?

How do we figure out what p should be if we don't know exactly what f looks like when sampling?

Is there a way to do this dynamically, i.e. if our function is just an input stream of data points?

How did we derive the graphs of f and p?

Is there a specific way that we can know p if we do not know what exactly is f like?

I am still a little confused. Where does this probability distribution p come from? Does it depend on the function f or the material of the object?

I am confused with why this works. If you can have a good estimate of p(x), doesn't this also mean that you have an estimate of f(x) and you can just solve for the integral?

How do we get f and p specifically?

After we switch our sample distribution, the biasness has not changed right? What about consistency?