How do I write a function in MATLAB that estimates the value between data points with Largrange interpolation?
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With amazing powers!!!
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Matlab, Gauss, S+ and probably a lot more.\n\nIn a pinch, you can also use MS-Excel.\nDownload this pdf file from Cliff Ragsdale´s book site:\nhttp://swlearning.com/quant/ragsdale/chapter12.exe\nIt actually works better than you´d think.\n\nOr go to http://swlearning.com/quant/ragsdale/fourth_edition/ragsdale.html\npick previous edition and student resource.
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hey!! chek out this website...\nBUT Y DO U WANT TO USE MATLAB FOR SEPARATING EVEN AND ODD?? THERE ARE OTHER METHODS...
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range = mean +- (t/sqrt(N))*st.dev.\n\nWhere t is found in a chart according to the confidence level in question, N is the number of data points, and st.dev. is the standard deviation of the data set.
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There is a primer here:\nhttp://www.phon.ucl.ac.uk/courses/spsci/matlab/primer40.pdf\n\nand an online course here:\nhttp://www.phon.ucl.ac.uk/courses/spsci/matlab/\n\nI may just be reviewing them myself!
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My TI-83plus can do that...but it has to be an invertible matrix.  If the determinate is zero, then it can not be done
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Map interpolation can be applied to a wide variety of data including 3-D data represented in 2-D (such as USGS topographic maps) and non-geographic datasets organized along any numerical coordinates. There are too many different algorithm types (such as bilinear, nearest-neighbor and B-spline) to describe them here. You might get a better answer if you could narrow your question to a specific kind of map or data. Also you can google "map interpolation" and browse the 5.5 million references.
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Through the fourier map generator.
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Prolog or Lisp. Machine learning\nMore detail please.\nI'm more for Java.\nBut most likely you are looking for the toolkit From MATLAB(tm) the first link.
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Take a look at the error function, and modify it so that you are dealing with distributions in 2 dimensions, using polar coordinates.\n\nFor example, the counterpart of the error function in 2 dimensions, in polar coordinates can actually be integrated, to produce the comulative distribution function\n\nF(R,s)=1-e^[-(R^2)/(2*s^2)]\n\nwhere s is the standard deviation, and R is the radius of a circle centered on the origin. \n\nAs R--> infinitity, then F(R,s)----> 1\nF(0,s)=0\n\nSuppose that the target has an edge R0 such that\n\nF(R0,s)=.5 for a given value of s. \n\nThen, you have to find the value of S for which F(R0,S)=0.9.
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Here's a couple of helpful sites:\nhttp://www.math.utah.edu/lab/ms/matlab/matlab.html\nhttp://www.indiana.edu/~statmath/math/matlab/\nhttp://www.mathworks.com/access/helpdesk/help/techdoc/matlab.shtml\n\nYou can do it... these are some useful sites. Just remember to properly define your search critera.\n\nHave fun.
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assign value for your x-variable...say -10, -5, 0, 5, 10 and repesent it in a graph form...
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There is a possible package at the bottom of the link.  But, why not just use some of the Matlab functions written by others and do it yourself?  Should be straightforward.
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so your scores will look like\n11 12 13 13 15 15 15 15 16 16 17 17 17 18 18 18 19 19 19 19 20 20 20 20 20 20 21 21 21 22 22 22 22 23 23 23 23 24 25 25\n\nthere are 40 observations, so Q1 is the (41/4=10.25)th observation, which is somewhere between 16 and 17\nusing linear interpolation, Q1 is 16.25
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numerical recipes in C.  Amazon has it.
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dx/dt+ax=b :P\n\n\nmathematica had some online find-the-derivitive program, last I remember
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Almost.  You would actually include the endpoints 0 and -3 (so you need to use a bracket instead of parentheses).\nD = [0, infinity)\nR = [-3, infinity)