Roy, Rui, Richard, Eric, thank you all so much!
Rui, you saw the date date2 issues and Roy, you were right!
I had Date2 in the test data and date2 in arima table after changing date to
date2 in the forecast piece.
Stepping through the pipeline found the other TYPO!! At geom_point(data =
test_tb
Thank you Roy, great suggestion, reviewing the link and trying steps now.
WHP
From: Roy Mendelssohn - NOAA Federal
Sent: Saturday, June 15, 2019 3:49 PM
To: Bill Poling
Cc: Richard M. Heiberger ; r-help (r-help@r-project.org)
Subject: Re: [R] Help with a third ggplot error
If I were a betti
So I changed it to date2.
fcast_arima_tbl <- forecast(fit_arima2, h = nrow(test_tbl)) %>%
sw_sweep(timetk_idx = TRUE, rename_index = "date2")
head(fcast_arima_tbl,n=10)
# A tibble: 10 x 7
date2 keyNetEditRev lo.80 lo.95 hi.80 hi.95 <--Date2
1 2017-01-01 actual
Oh, yikes! Rui you are right.
1st I do this:
fit_arima2 <- train_tbl %>%
tk_ts(select = NetEditRev, frequency = 364) %>%
Arima(order = c(1,0,2), #this may be arima not Arima?
seasonal=c(0,1,0),
include.drift = TRUE)
Then when I use the forecast and sweep function I changed it
Hello,
Inline.
Às 20:29 de 15/06/19, Bill Poling escreveu:
Hello Richard, thank you for your response.
Here is what I get with your suggestion, however, I am unsure of what I am
looking at, perhaps you can interpret.
I sure appreciate your help Sir!
g4 <- fcast_arima_tbl1 %>%
ggplot(aes(
If I were a betting man I would bet that one of the things in your "pipeline"
isn't returning what you think it is. You can either break it out step by step
to check or this page lists a variety of resources to debug pipes:
https://www.rostrum.blog/2019/04/07/fix-leaky-pipes/
HTH,
-Roy
> On
Yes, thank you I see that now Eric.
What might I provide in addition that would be more useful?
WHP
From: Bill Poling
Sent: Saturday, June 15, 2019 3:39 PM
To: Eric Berger
Cc: r-help (r-help@r-project.org) ; Bill Poling
(bill.pol...@zelis.com)
Subject: RE: [R] Help with a third ggplot error
Hello Richard, thank you for your response.
Here is what I get with your suggestion, however, I am unsure of what I am
looking at, perhaps you can interpret.
I sure appreciate your help Sir!
g4 <- fcast_arima_tbl1 %>%
ggplot(aes(date, NetEditRev, color = key)) + #Now date due to sweep
geom_
reprex = reproducible example
On Sat, Jun 15, 2019 at 10:20 PM Bill Poling wrote:
> Hello Eric.
>
> I am unfamiliar with the term reprex, however, I am googling it now.
>
> In the meantime, here is the source DF sample and the train test code I
> sure hope it helps.
>
> head(dftmp,n=7)
> Date2 N
Hello Eric.
I am unfamiliar with the term reprex, however, I am googling it now.
In the meantime, here is the source DF sample and the train test code I sure
hope it helps.
head(dftmp,n=7)
Date2 NetEditRev index.num year half quarter month.lbl day wday.lbl holiday
1 2017-01-01-923.40 148
you did something like this:
> mydf <- data.frame(y=1:16,
+AA=rep(factor(letters[1:8]), 2),
+BB=rep(factor(LETTERS[12:13]), each=8),
+CC=rep(factor(rep(LETTERS[9:11], times=c(3,1,4))), 2))
> ggplot(mydf, aes(ls, y))
Don't know how to auto
Is this supposed to be a reprex? I don't see where train_tbl is defined.
On Fri, Jun 14, 2019 at 10:30 PM Bill Poling wrote:
> #RStudio Version 1.2.1335
> sessionInfo()
> #R version 3.5.3 (2019-03-11)
> #Platform: x86_64-w64-mingw32/x64 (64-bit)
> #Running under: Windows >= 8 x64 (build 9200)
>
Hi Morgan,
In the example, please ignore
`C_set_altrep_subset_method("compressedMatrix", get_subset_func)`. You do
not have to define it to run the example.
Best,
Jiefei
On Sat, Jun 15, 2019 at 11:45 AM King Jiefei wrote:
> Hi Morgan,
>
> Thanks for the context, it seems like you want to compr
Hi Morgan,
Thanks for the context, it seems like you want to compress your matrix and
you expect the "new" matrix should contain the same amount of information
as the "old" one, it is correct?
If this is the case, since you are using C++ code, a safer but imperfect
solution is to find a C++ data
Hi Jiedei,
Thank you for your reply.
To give you a bit more context, I wrote a function that find all the
positions (index) of all small matrices inside a larger matrix. At the
beginning I pre-allocate let's say a 100 by 2 matrix. However a lot of
values might remain empty in this matrix of posti
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