Recent content by Whenry

Thank you, I had thought I had posted a response but I do not see it here... anyways, I think my friend helped me see the difference. He offered a much more robust definition of the chain rule...more than I would type out in latex here. However, I can say the following. The "chain rule"...

Ok...one last example that I have found on an MIT video. (The video is short and this is example is done in the first five minutes, it is here. They also try and relate it to a total derivative. The example is: Suppose Z = x^2 + y^2 {\rm and }\,\, x = u^2 - v^2 {\rm and }\,\, y= uv ...

This makes sense to me. But, I have trouble reconciling that explanation with the partial derivative chain rule. An example is at the top of the pdf linked here. It seems that w only explicitly depends on x and y, but the partial derivative w.r.t t is non-zero. I really appreciate you taking...

The reason this is confusing to me is that I have seen the chain rule applied to partial derivatives, which lead me to think you could take something like \frac{\partial F(x(\epsilon))}{\partial \epsilon} = \frac{\partial F(x(\epsilon))}{\partial x}\frac{\partial x}{\partial \epsilon}

The reason this is confusing to me is that I have seen the chain rule applied to partial derivatives, which lead me to think you could take something like \frac{\partial F(x(\epsilon))}{\partial \epsilon} = \frac{\partial F(x(\epsilon))}{\partial x}\frac{\partial x}{\partial \epsilon} x

Hello all, I am having some frustration understanding one derivation of the Euler Lagrange Equation. I think it most efficient if I provide a link to the derivation I am following (in wikipedia) and then highlight the portion that is giving me trouble. The link is here If you scroll...

Thank you chiro, I appreciate your feedback. I have been doing some investigating into Bayesian inference and seems that I will have to have some data points within the distribution h(x|b,c) in order to infer the paramaters of the distribution. Unfortunately, I will have very few to none of...

I do have experience coding naive bayes binomial classifiers, but that is where my experience ends. I certainly have no experience using bayesian inference to arrive at PDFs of continuous variables, as is x in the above example. Neither do I have experience with MCMC. I will need to find...

Thank you Chiro, I apologize for lack of clarity. I mean the following cases (I am not sure of the proper notation): f(x|B) means the distributions of x given B and (C or not C). g(x|C) means the distributions of x given C and (B or not B). h(x|B,C) means the distributions of x given...

Hi all, My question is the following. Let's say I have two probability distributions; f(x|b)\,g(x|c) b and c are discrete events while x is a continuos variable. i.e When the button b is pressed there is some distribution for the amount of rain fall the next day, x. When the button c...

chiro, thank for your time and advice... could you explain this a little more; especially in the context of logistic regression. I have 50 yr time series where b_1 > 0 and statistically sig, p < 0.05 but for years 40 to 50 b_1 < 0 and stat sig. So if I am trying to add an interaction...

I am using MatLab. But I have used R as well and could use that if it would be a good tool. I have a fairly good amount of numerical experience and dynamical systems experience, but my experience with statistics is not as strong...although I did have a year of grad level...I need practice...

How do I handle the following situation. I have two time series, A and B. For the entire 100 yrs, we have P(A|B) ≠P(A), and Chi squared test leads us to reject the hypothesis of independence. But, If I break the data down into 10 yr chucks, I find that for some 10 yr chucks P(A|B) = P(A)...

Hi all, I would like to understand the theory for determining outliers in the following scenario. Let's say I am to fit a linear model to the data of house size v. sale price for a particular location. And let's say I have a fairly good linear relationship, as house size increases, so does...

Hi all, I am using a Xi squared test to for independence of two sets of categorical data. So let's say I have a vector x1 of 1s and 0s and x2 of 1s and 0s, and I am testing to see if x1 and x2 are independent. and let's say, for my given data, with n = 200, I have x1=1...