search for: glenb

...cr*wup in line(). Notice, incidentally, that > line(1:9+rnorm(9,,1e-1),1:9+rnorm(9,,1e-1)) Call: line(1:9 + rnorm(9, , 0.1), 1:9 + rnorm(9, , 0.1)) Coefficients: [1] -0.9407 1.1948 I.e., it is not likely an issue with exact integers or perfect fit. -pd > On 29 May 2017, at 07:21 , GlenB <glnbrntt at gmail.com> wrote: > >> Tukey divides the points into three groups, not the x and y values > separately. > >> I'll try to get hold of the book for a direct quote, might take a couple > of days. > > Ah well, I can't get it for a week. But th...

Tukey divides the points into three groups, not the x and y values separately. I'll try to get hold of the book for a direct quote, might take a couple of days. On Mon, May 29, 2017 at 8:40 AM, Duncan Murdoch <murdoch.duncan at gmail.com> wrote: > On 27/05/2017 9:28 PM, GlenB wrote: > >> Bug: stats::line() does not produce correct Tukey line when n mod 6 is 2 >> or >> 3 >> >> Example: line(1:9,1:9) should have intercept 0 and slope 1 but it gives >> intercept -1 and slope 1.2 >> >> Trying line(1:i,1:i) across a range of...

...: >> line(1:9 + rnorm(9, , 0.1), 1:9 + rnorm(9, , 0.1)) >> >> Coefficients: >> [1] -0.9407 1.1948 >> >> I.e., it is not likely an issue with exact integers or perfect fit. >> >> -pd >> >> >> >>> On 29 May 2017, at 07:21 , GlenB <glnbrntt at gmail.com> wrote: >>> >>>> Tukey divides the points into three groups, not the x and y values >>> separately. >>> >>>> I'll try to get hold of the book for a direct quote, might take a couple >>> of days. >>&gt...

I have an additive model of the following form : zmdlfit <- lm(z~ns(x,df=6)+ns(y,df=6)) I can get the fitted values and plot them against z easily enough, but I also want to both obtain and plot the two additive components (the estimates of the two additive terms on the RHS) I've been looking at manuals and searching on the internet and searching the archives, but I'm apparently

...1:9+rnorm(9,,1e-1),1:9+rnorm(9,,1e-1)) > Call: > line(1:9 + rnorm(9, , 0.1), 1:9 + rnorm(9, , 0.1)) > > Coefficients: > [1] -0.9407 1.1948 > > I.e., it is not likely an issue with exact integers or perfect fit. > > -pd > > > >> On 29 May 2017, at 07:21 , GlenB <glnbrntt at gmail.com> wrote: >> >>> Tukey divides the points into three groups, not the x and y values >> separately. >> >>> I'll try to get hold of the book for a direct quote, might take a couple >> of days. >> >> Ah well, I can...

...rnorm(9, , 0.1)) >>> >>> Coefficients: >>> [1] -0.9407 1.1948 >>> >>> I.e., it is not likely an issue with exact integers or perfect fit. >>> >>> -pd >>> >>> >>> >>>> On 29 May 2017, at 07:21 , GlenB <glnbrntt at gmail.com> wrote: >>>> >>>>> Tukey divides the points into three groups, not the x and y values >>>> separately. >>>> >>>>> I'll try to get hold of the book for a direct quote, might take a couple >>>&...

Bug: stats::line() does not produce correct Tukey line when n mod 6 is 2 or 3 Example: line(1:9,1:9) should have intercept 0 and slope 1 but it gives intercept -1 and slope 1.2 Trying line(1:i,1:i) across a range of i makes it clear there's a cycle of length 6, with four of every six correct. Bug has been present across many versions. The machine I just tried it on just now has R3.2.3:

...k for a direct quote, might take a couple of days. Ah well, I can't get it for a week. But the fact that it's often called Tukey's three group line (try a search on *tukey three group line* and you'll get plenty of hits) is pretty much a giveaway. On Mon, May 29, 2017 at 2:19 PM, GlenB <glnbrntt at gmail.com> wrote: > Tukey divides the points into three groups, not the x and y values > separately. > > I'll try to get hold of the book for a direct quote, might take a couple > of days. > > > > On Mon, May 29, 2017 at 8:40 AM, Duncan Murdoch &lt...

On 27/05/2017 9:28 PM, GlenB wrote: > Bug: stats::line() does not produce correct Tukey line when n mod 6 is 2 or > 3 > > Example: line(1:9,1:9) should have intercept 0 and slope 1 but it gives > intercept -1 and slope 1.2 > > Trying line(1:i,1:i) across a range of i makes it clear there's a cycle of &...

I found the old ace function (from acepack) valuable a couple of years ago in helping to find a transformation of the response to approximate additivity in smooth functions of the predictors. ace used alternating conditional expectations, but I'm not overly fixated on algorithms as long as it works pretty well. Is there another package that has that sort of functionality? I haven't been

Hi everyone, Suppose I have a list named "lst", see below: > lst $sub1 ... $sub1$x ... $sub1$y .... $sub2 ... $sub2$x ... $sub2$y ? $sub3 ... ... ... Now, I want to extract the sub-sublist $y from every sublist(sub1, sub2...) and then storage them to a new list. I know how to extract them by subscript or list name one by one, but I wonder if there exist some tricks to finish this