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...place to look at. I have a multidimensional piece-wise regression linear problem, i.e. to find not only the regression coefficients for each "interval" but also the beginning and ends of the intervals. To simplify it to the one dimensional case and two intervals, the problem is to find A_0, A_1, ... A_p and "C" from the given sample, assuming the curve is like this: A_0*f_0(x)+A_1*f_1(x)+ ... + A_p*f_p(x) with x < C A_0'*f_0(x)+A_1'*f_1(x)+ ... + A_p'*f_p(x) with x >= C Functions f_1, f_2, ... f_p are known. Is there anything in R for that? I have tri...

...uld have collinearity problems, so I decided to do a partial regression to predict y. I did it this way: - I regressed y to A, and calculated the residuals (e_y) (reg1) - I regressed x to A, and calculated the residuals (e_x) (reg2) - I regressed e_y to e_x (reg5) It looks like this: y = a_0 + a_1 A (reg1) x = b_0 + b_1 A (reg2) e_y = y - (a_0 + a_1 A) (3) e_x = x - (b_0 + b_1 A) (4) e_y = beta_0 + beta_1 e_x (reg5) Then, to predict a y_0 from a new x_0 and A_0, we would: Calculate e_x0 with the equation (4). Calculate e_y0 with the equation (reg5) and then: y_0 = e_y0 + (a_0 + a_1 A_0...

Dear R-Users, I need to find a smooth function f() and coefficients a_i that give the best fit to y ~ a_0 + a_1*f(x_1) + a_2*f(x_2) Note that it is the same non-linear transformation f() that is applied to both x_1 and x_2. So my first question is how can I do it in R? A more general question is this: suppose I have a utility function U(a_i, f()), where f() is say a spline. Is there a general optimi...

Hi, It is my understanding that the eigenvectors of a circulant matrix are given as follows: 1,omega,omega^2,....,omega^{p-1} where the matrix has dimension given by p x p and omega is one of p complex roots of unity. (See Bellman for an excellent discussion on this). The matrix created by the attached row and obtained using the following commands indicates no imaginary parts for the

Hi R-helpers, I'm new to time series modelling, but my requirement seems to fall just outside the capabilities of the arima function in R. I'd like to fit an ARMA model where the variance of the disturbances is a function of some exogenous variable. So something like: Y_t = a_0 + a_1 * Y_(t-1) +...+ a_p * Y_(t-p) + b_1 * e_(t-1) +...+ b_q * e_(t-q) + e_t, where e_t ~ N(0, sigma^2_t), and with the variance specified by something like sigma^2_t = exp(beta_t * X_t), where X_t is my exogenous variable. I would be very grateful if somebody could point me in the direction...

...the "teacher effect" applies to only one year. One can think of the first score on the student as a score from a prior year (for which I have no teacher links), and the second score is from the current year and is linked to the teacher. The model for student j in class i is: Y_{ij0} = a_0 + e_{ij0} Y_{ij1} = a_1 + b_i + e_{ij1} with Var(b_i) the teacher variance component and Cov(e_{ij0},e_{ij1}) unstructured. That is, if the data are organized by student, the "Z" matrix in the usual linear mixed model notation has every other row equal to a row of zeros. I am wondering...

When you say that distribution shouldn't be used, do you mean within instcombine rather than some other pass? Or not all as an IR optimization? A dedicated optimization pass that looks for and makes factoring/distribution folds to eliminate instructions seems like it would solve the problems that I'm seeing. Ie, I'm leaning towards the proposal here: https://reviews.llvm.org/D41574

...00000] at ak+a.f () [0x00000] at af.b () [0x00000] at Microsoft.VisualBasic.ApplicationServices.WindowsFormsApplicationBase.OnRun () [0x00000] at Microsoft.VisualBasic.ApplicationServices.WindowsFormsApplicationBase.Run (System.String[] commandLine) [0x00000] at af.a (System.String[] A_0) [0x00000] This program is for debate research, and I really need it to work! Thanks for your help! -The Moose

Dear R people: Is there a way to perform simple polynomial multiplication; that is, something like (x - 3) * (x + 3) = x^2 - 9, please? I looked in poly and polyroot and expression. There used to be a package that had this, maybe? thanks, Erin -- Erin Hodgess Associate Professor Department of Computer and Mathematical Sciences University of Houston - Downtown mailto: erinm.hodgess at

> On May 8, 2018, at 9:50 AM, Daniel Berlin via llvm-dev <llvm-dev at lists.llvm.org> wrote: > > 1. The reassociate pass that exists right now was *originally* (AFAIK) written to enable CSE/GVN to do better. Agreed. The original mindset included a (naive) belief that going with a canonical form was better than teaching redundancy elimination to handle abstractions (as a matter

...800); +/* + * This can be a bit difficult to understand at first glance. Reg + * combiners are described here: + * http://icps.u-strasbg.fr/~marchesin/perso/extensions/NV/register_combiners.html + * + * Single texturing setup, without honoring vertex colors (non default + * setup) is: Alpha RC 0 : a_0 * 1 + 0 * 0 RGB RC 0 : rgb_0 * 1 + 0 * + * 0 RC 1s are unused Final combiner uses default setup + * + * Default setup uses vertex rgb/alpha in place of 1s above, but we + * don't need that in 2D. + * + * Multi texturing setup, where we do TEX0 in TEX1 (masking) is: + * Alpha RC 0 : a_0 * a_1 +...

...ction(facvec,base.lm){ if ( missing(facvec) || missing(base.lm) ){ cat("This script assesses the contribution of terms in a lm model.\n") cat(" It expects a vector of names and a lm.object to update.\n") cat(" as in script.name(facvec,base.lm).\n") stop() } a_0 i_0 base.r2_summary(base.lm)$r.squared for (i in 1:length(facvec)){ a[i]_c(fac=summary(update(base.lm,.~.+as.name(facvec[i])))$r.squared-base.r2) i_i+1 } return(a) } Thanks for any help, adrian acuster at nature.berkeley.edu -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-....

...tivation (online fails), the application starts, but gives the error: Code: System.MissingMethodException: Method not found: Int32 SkySoftware.FileViewControl.FileView.get_SelectedCount(). at a.a.c.a.a.h.b() at a.a.c.a.a.f.a() at a.a.c.a.a.i.b() at a.a.o.b.d() at a.a.o.b.ab(Object A_0, EventArgs A_1) at System.Windows.Forms.Form.OnLoad(EventArgs e) at System.Windows.Forms.Form.OnCreateControl() at System.Windows.Forms.Control.CreateControl(Boolean fIgnoreVisible) at System.Windows.Forms.Control.CreateControl() at System.Windows.Forms.Control.WmShowWindow(Message&a...

Hi, could anyone tell me how predict() predicts the new value(s), of a MA(1) arima-modell. its really easy to make it with an AR(1), knowing the last term, but how can i or R know the last error? It would also help if somebody could tell me how to find the "open" source of the function predict(). Thanks and sorry for my poor english. -- View this message in context:

Here is the error I recieved upon running it through shell, any ideas? err:ole:CoGetContextToken apartment not initialised fixme:shell:URL_ParseUrl failed to parse L"Apex.Integration" fixme:shell:URL_ParseUrl failed to parse L"System" fixme:shell:URL_ParseUrl failed to parse L"System.Windows.Forms" fixme:shell:URL_ParseUrl failed to parse L"System.Drawing"

...k+1 \over 8N} \pi b_k o c_k = \sum_{j=0}^{2N-1} a_j ( \cos{(2k+1)(j) \over 4N} \pi + \cos{(2k+1)(j+1) \over 4N} \pi ) c_k = \sum_{j=0}^{2N-1} a_j \cos{(2k+1)(j) \over 4N} \pi + \sum_{j=1}^{2N-1} a_{j-1} \cos{(2k+1)(j) \over 4N} \pi Now set a'_j := a_j + a_{j-1} (but a'_0 = a_0) then c_k = \sum_{j=0}^{2N-1} a'_j \cos{(2k+1)(j) \over 4N} \pi This is a DCT-II. We can split it: c_k = \sum_{j=0}^{N-1} a'_{2j} \cos{(2k+1)(j) \over 2N} \pi + \sum_{j=0}^{N-1} a'_{2j+1} \cos{(2k+1)(2j+1) \over 4N} \pi (for k < N), and c_(2N-1-k} = \sum_{j=0}^{N-1} a'_{...

...B is delayed so that the compiler can speculatively execute these operations and there's only full UB if the result is somehow "consumed". 2) Undef was created to represent uninitialized memory reads. For example, it's very useful in conjunction with PHI nodes: int a; if (foo) a_0 = 42; a_1 = phi(a_0, undef) By using undef, we don't have to materialize some arbitrary constant on a branch where a variable is not initialized. 3) And then people realized that undef wasn't enough. For example, we'd also like to be able to optimize expressions like "((a + 1) &...

...B is delayed so that the compiler can speculatively execute these operations and there's only full UB if the result is somehow "consumed". 2) Undef was created to represent uninitialized memory reads. For example, it's very useful in conjunction with PHI nodes: int a; if (foo) a_0 = 42; a_1 = phi(a_0, undef) By using undef, we don't have to materialize some arbitrary constant on a branch where a variable is not initialized. 3) And then people realized that undef wasn't enough. For example, we'd also like to be able to optimize expressions like "((a + 1) &...