similar to: grid search with failed evaluations (and nonlinear start values as a secondary consideration)

Hi, this is purely a time series question if anyone has a hint. I'm trying to complex demodulate a series at different frequencies. Say at $\lambda$ = 1/100, 1/41 and 1/23. (These correspond to various astronomical forcing frequencies of ice ages, incidentally). Now, following say Hasan (1982, Hand. of Stats) or Brillinger (1987, Fitting Cosines), I do the following: 1. from y, form the

Hi everybody, I have a problem with a cluster analysis. I am trying to use hclust, method=ward. The Ward method works with SQUARED Euclidean distances. Hclust demands "a dissimilarity structure as produced by dist". Yet, dist does not seem to produce a table of squared euclidean distances, starting from cosines. In fact, computing manually the squared euclidean distances from cosines

+ Hello, The parametric equations of an ellipsoid can be written in terms of spherical coordinates. The three spherical coordinates are converted to Cartesian coordinates by X=a cos (α) sin(θ) Y=b sin(α) sin(θ) Z=c cos(θ) for α and θ The parameter α varies from 0 to 2 π and θ varies from 0 to π . Here ( X o , Y o ,Z o ) is the center of the ellipsoid, and θ is the angle

I am having following problem: I?m constructing model for calculation of area of triangle. I know sides a, b, and gamma angle. I wish to calculate the area using heron?s formula: S <- sqrt(s*(s-a)*(s-b)*(s-c)) where s <- (a+b+c)/2 and c is calculated using law of cosines: c <- sqrt(a^2 + b^2 -2*a*b*cos(gamma)) since i am calculating a regression model, i need derivation of this

Hello, I'm plotting two sets of data referenced to either the left or right y-axes. The first, water table depth (blue circles), is plotted on the left y-axis in reverse order (0 at the top) as this is more intuitive when thinking in terms of depth. The second is electrical conductance (a surrogate for salinity), and is referenced to the right y-axis. The data and plot commands follow

My wife has been using a diagnostic from Manley (1991; "Randomization and MonteCarlo Methods in Biology") that compares a normal multiple regression's performance with that using random predicted variables. Is there something like this already available in R? If not, the "boot" package looks like a good place to start looking for methods, no? Thanks in advance Bruce

Hi all, I wanted to make sure that I am getting the most from my 8 core computer running R. I have a distance function like this: distance <- function(pointX, pointY, vecX, vecY) { #convert everything to radians pointX = pointX * pi/180 pointY = pointY * pi/180 vecX = vecX * pi/180 vecY = vecY * pi/180 #data@coords[,2] = lat #data@coords[,1] = lon delta_lon = pointX - vecX

Dear, I am trying to visualise a time-progressing line (it's supposed to represent spread patterns) using brew package and Google Earth. The idea is to have a function which takes start and end point geographic coordinates, as well as number of intervals to chop the path up, and returns the collection of points segmenting this line. Unfortunately my calculations fail for large distances,

Hi everyone (again), before you all start screaming that the reordering of factors has been discusse on several threads and is not particular to ggplot2, hear me out. I can easily reorder my x-axis factor in facet.grid() in ggplot2. What I cannot reorder are the factors represented on the strips. I can see that the graphs are changing, so I am afraid of what it is I am doing. Why is ggplot2

This e-mail - summarizes some of the responses/suggestions to using R for 13 year olds from my query on this list - discusses some additional investigation I did - the approach I am currently using (which will likely incorporate your suggestions for R) SUGGESTIONS - find relationship between monthly heating bills and temperature. For data see

Hello, a. is there a possibility to obtain a distance matrix with the cosine between vectors?? hclust, hierclust, dist will not work and seem to be hard to extend. b. if there is not: Is the cosine between vectors implemented somewhere? Thanks for all hints and advice! Petra Steiner -------------- next part -------------- An HTML attachment was scrubbed... URL:

Thank you so much Dr. Nash, I truly appreciate your kind and valuable contribution. Cheers, Paul El El s?b, 19 de ago. de 2023 a la(s) 3:35 p. m., J C Nash < profjcnash at gmail.com> escribi?: > Why bother. nlsr can find a solution from very crude start. > > Mixture <- c(17, 14, 5, 1, 11, 2, 16, 7, 19, 23, 20, 6, 13, 21, 3, 18, 15, > 26, 8, 22) > x1 <- c(69.98, 72.5,

Optimize celt_pitch_xcorr function (for fixed point). Even though same code in theory should work for ARMv7 as well, turning this on only for aarch64 at the moment since there is a fixed point asm implementation for ARMv7 neon. Signed-off-by: Viswanath Puttagunta <viswanath.puttagunta at linaro.org> --- celt/arm/celt_neon_intr.c | 268 ++++++++++++++++++++++++++++++++++++++++++++++

Optimize celt_pitch_xcorr function (for fixed point). Even though same code in theory should work for ARMv7 as well, turning this on only for aarch64 at the moment since there is a fixed point asm implementation for ARMv7 neon. Signed-off-by: Viswanath Puttagunta <viswanath.puttagunta at linaro.org> --- celt/arm/celt_neon_intr.c | 268 ++++++++++++++++++++++++++++++++++++++++++++++

Dear friends, This is the dataset I am currently working with: >dput(mod14data2_random) structure(list(index = c(14L, 27L, 37L, 33L, 34L, 16L, 7L, 1L, 39L, 36L, 40L, 19L, 28L, 38L, 32L), y = c(0.44, 0.4, 0.4, 0.4, 0.4, 0.43, 0.46, 0.49, 0.41, 0.41, 0.38, 0.42, 0.41, 0.4, 0.4 ), x = c(16, 24, 32, 30, 30, 16, 12, 8, 36, 32, 36, 20, 26, 34, 28)), row.names = c(NA, -15L), class =

Dear friends, Hope you are all doing well and having a great weekend. I have data that was collected on specific gravity and spectrophotometer analysis for 26 mixtures of NG (nitroglycerine), TA (triacetin), and 2 NDPA (2 - nitrodiphenylamine). In the dataset, x1 = %NG, x2 = %TA, and x3 = %2 NDPA. The response variable is the specific gravity, and the rest of the variables are the predictors.

Optimize celt_pitch_xcorr function (for floating point) using ARM NEON intrinsics for SoCs that have NEON VFP unit. To enable this optimization, use --enable-intrinsics configure option. Compile time and runtime checks are also supported to make sure this optimization is only enabled when the compiler supports neon intrinsics. --- Makefile.am | 12 ++

On 19 December 2014 at 17:25, Viswanath Puttagunta <viswanath.puttagunta at linaro.org> wrote: > Optimize celt_pitch_xcorr function (for floating point) > using ARM NEON intrinsics for SoCs that have NEON VFP unit. > > To enable this optimization, use --enable-intrinsics > configure option. > > Compile time and runtime checks are also supported to make sure > this

Optimize celt_pitch_xcorr function (for floating point) using ARM NEON intrinsics for SoCs that have NEON VFP unit. To enable this optimization, use --enable-intrinsics configure option. Compile time and runtime checks are also supported to make sure this optimization is only enabled when the compiler supports neon intrinsics. --- Makefile.am | 11 ++

Optimize celt_pitch_xcorr function (for floating point) using ARM NEON intrinsics for SoCs that have NEON VFP unit. To enable this optimization, use --enable-intrinsics configure option. Compile time and runtime checks are also supported to make sure this optimization is only enabled when the compiler supports neon intrinsics. --- Makefile.am | 12 ++