I've got this request: Using any alphabetical and numerical symbols, define a code in which each symbol of interest is associated with the corresponding binary configuration. The code must use 5 bits, be redundant, and be characterized by a Hamming distance of 1. Identify the cardinality of the defined code. Eventually, does the code exist?
I don't have a clear idea about how to do this, could anyone help?
Thank you!
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I'm working on a simple project in which I'm trying to describe the relationship between two positively correlated variables and determine if that relationship is changing over time, and if so, to what degree. I feel like this is something people probably do pretty often, but maybe I'm just not using the correct terminology because google isn't helping me very much.
I've plotted the variables on a scatter plot and know how to determine the correlation coefficient and plot a linear regression. I thought this may be a good first step because the linear regression tells me what I can expect y to be for a given x value. This means I can quantify how "far away" each data point is from the regression line (I think this is called the squared error?). Now I'd like to see what the error looks like for each data point over time. For example, if I have 100 data points and the most recent 20 are much farther away from where the regression line/function says it should be, maybe I could say that the relationship between the variables is showing signs of changing? Does that make any sense at all or am I way off base?
I have a suspicion that there is a much simpler way to do this and/or that I'm going about it in the wrong way. I'd appreciate any guidance you can offer!
I can suggest two strands of literature that study changing relationships over time. Typing these names into google should provide you with a large number of references so I'll stick to more concise descriptions.
(1) Structural break modelling. As the name suggest, this assumes that there has been a sudden change in parameters (e.g. a correlation coefficient). This is applicable if there has been a policy change, change in measurement device, etc. The estimation approach is indeed very close to the procedure you suggest. Namely, you would estimate the squared error (or some other measure of fit) on the full sample and the two sub-samples (before and after break). If the gains in fit are large when dividing the sample, then you would favour the model with the break and use different coefficients before and after the structural change.
(2) Time-varying coefficient models. This approach is more subtle as coefficients will now evolve more slowly over time. These changes can originate from the time evolution of some observed variables or they can be modeled through some unobserved latent process. In the latter case the estimation typically involves the use of state-space models (and thus the Kalman filter or some more advanced filtering techniques).
I hope this helps!
I am calculating a variance-covariance matrix and I see two different ways of calculating the standard errors:
sqrt(diagonal values/number of observations)
e.g. standard deviation / sqrt(number of observations)
(as is given from on how to calculate the standard error https://en.wikipedia.org/wiki/Standard_error)
or some people say it is simply
sqrt(diagonal values)
I had previously thought that the diagonal values in the variance-co-variance matrix were the variance and hence the square root would be the standard deviation (not the SE). However, the more I read the more I think I may be wrong and that it is the SE, but I am unsure why this is the case.
Can anyone help? Many thanks!!
Yes, the diagonal elements of the covariance matrix are the variances. The square root of these variances are the standard deviations. If you need the standard error you have to clarify the question "the standard error of what?" (see also the wikipedia entry of your post). If you mean the standard error of the mean then yes, "standard deviation / sqrt(number of observations)" is what you are looking for.
so here is my situation. I have to solve a math problem on server end and could expect tens of thousands of requests a second so I'm trying to find the most efficient path to solving the problem.
Client will submit some number, let's call it A, and I need to determine base of the exponent in a geometric series (see below) where the result will be as close to A as possible without exceeding it.
The problem is that in the real-world, each value of the geometric series is rounded, so standard math can't apply.
round(x^1)+round(x^2)+round(x^3).
I can use the partial sum of geometric series equation to find some rough upper and lower limits using:
((x)^(n+1)-1)/((x)-1)
So say x=2 is a lower limit and x=2.03 is an upper limit... and the value i'm solving for is x=2.02392372838123.
So far the only solution i found was to use a recursive function to go through decimals individually testing until I find the number, but the load on the server is too high at the volume of requests I expect. (I am using node.js).
Does anyone have any thoughts or suggestions on a more efficient way to solve this? Again the only reason I can't solve this with math alone (to the best of my skill) is because of the real-world rounding of numbers in the sum.
Thanks.
The term interpolation is usually used in mathematical functions when determining a function for given values, which makes perfect sense. I don't see how that applies for strings, what is being interpolated? Am I missing something obvious?
Interpolation in mathematics is simply working out the things between two points(a). For example, cubic spline fitting over a series of points will give you a curve of some description (I consider a straight line to be a degenerate curve here so don't bother pointing out that some formulae generate such a beast) between each set of points, even though you have no actual data there.
Contrast this with extrapolation which will give you data beyond the endpoints. An example of that is seeing that, based on history, the stock market indices rise at x percent per annum so, in a hundred years, will be much higher than they are now.
So it's a short step to the most likely explanation as to why variable substitution within strings is called interpolation, since you're changing things within the bounds of the data:
xyzzy="42"
plugh="abc${xyzzy}xyz"
// now plugh is equal to "abc42xyz"
(a) The actual roots of the word are Latin inter + polare, those translating to "within" and "polish" (in the sense of modify or improve). See here for more detail.
For example the light source is coming from 1,3,-5 and object is at 4,-2,-1.
Algebraic formula is going to give the answer as 3. [1,3-5].[4,-2,-1]
= 1*4 + 3*-2 + -5*-1 = 3
But what does this 3 means? How do I know if my object is shaded with this number 3? Or is there more to it? I did look around and unable to find anything conclusive. Would be great if someone could give some insight. Thank you.
Judging from answers, pondering if I am understanding my question wrong. I was trying to get my head around the following question:
For a point on a convex surface, with the normal n=(n1,n2,n3)and light
direction l = (l1,l2,l3), determine if the point can be seen by light
source.
Using a dot product between two points makes no sense. Essentially, a dot product gives a measure of how similar two vectors are. When applied to points, the value will be related to the similarity of the direction to the points from the origin, as well as their distance from it. That metric doesn't make much sense, as you found out with that '3'.
To determine the amount of illumination, you want to be using a dot product between the normalized vector of the direction from the surface to the light and the surface normal. The result will be a value from -1 to 1, which you can interpret as an illumination factor for simple gouraud shading. In pseudocode:
illumination = max(0, dot(normalize(lightPosition - positionOnSurface), surfaceNormal))
Determining if a light hits an object is an entirely different problem called occlusion, and not really something you express in as mathematical formula. It's about testing what objects are in the path from the light to your target object.
The dot product can tell you on what side of a line a point is. The triangle is formed by three lines. If you are on the same side of all three lines then you are inside the triangle. You can use three dot products to test for each of the three sides. See slide 23 on this link http://comp575.web.unc.edu/files/2010/09/06raytracing1.pdf.