Thank you so much David!
El El vie, 22 de abr. de 2022 a la(s) 11:04 p. m., David Carlson <
dcarl...@tamu.edu> escribió:
> Since the rolls are independent, it is not necessary to separate the rolls
> into two stages:
>
> sides <- 6
> months <- 12
> reps <- 100
>
> set.seed(2022)
> results <- matrix(sample.int(sides, months*reps, replace=TRUE), reps,
> months, byrow=TRUE)
> colnames(results) <- month.name
> all6 <- apply(results, 1, function(x) length(intersect(x, 1:6))==6)
> sum(all6)/reps
> # 0.53 which matches Rui's result
> results <- as.data.frame(results)
>
> David L. Carlson
>
>
>
> On Thu, Apr 21, 2022 at 4:04 AM Rui Barradas <ruipbarra...@sapo.pt> wrote:
>
>> Hello, There's an error in my code, inline. Às 07:55 de 21/04/2022, Rui
>> Barradas escreveu: > Hello, > > For what I understand of the question, the
>> followng might answer it. > > The functions below roll dice and simulate R
>> replicates
>> ZjQcmQRYFpfptBannerStart
>> This Message Is From an External Sender
>> This message came from outside your organization.
>>
>> ZjQcmQRYFpfptBannerEnd
>>
>> Hello,
>>
>> There's an error in my code, inline.
>>
>> Às 07:55 de 21/04/2022, Rui Barradas escreveu:
>> > Hello,
>> >
>> > For what I understand of the question, the followng might answer it.
>> >
>> > The functions below roll dice and simulate R replicates of dice rolls.
>> > Then 12 (one per month) 6 sided dice rolls are simulated 100 times.
>> >
>> > The colMeans/apply computes the empiric probabilities of having all 6
>> > sides occur in each row, Jan to Dec and a overall probabilty is the mean
>> > of those probabilities.
>> >
>> > The matrix is coerced to data.frame only at the end.
>> >
>> >
>> >
>> > dice <- function(rolls = 1, ndice = 1, sides = 6) {
>> > roll <- function(ndice = 1, sides = 6) {
>> > sample(seq_len(sides), ndice, replace = TRUE)
>> > }
>> > y <- replicate(rolls, roll(ndice = ndice, sides = sides))
>> > if(is.null(dim(y))) y else colSums(y)
>> > }
>> > dice_simul <- function(rolls = 1, ndice = 1, sides = 6, R) {
>> > if(missing(R)) {
>> > stop("number of simulations 'R' is missing with no default.")
>> > }
>> > replicate(R, dice(rolls = rolls, ndice = ndice, sides = sides))
>> > }
>> >
>> > dice_rolls <- 100
>> > #dice_rolls <- 1e6
>> > num_dice <- 1
>> > dice_sides <- 6
>> > months <- 12
>> >
>> > set.seed(2022)
>> > prob_frame <- t(dice_simul(months, num_dice, dice_sides, R = dice_rolls))
>> > colnames(prob_frame) <- month.name
>> > head(prob_frame)
>> >
>>
>> # --- wrong
>> > p <- colMeans(apply(prob_frame, 1, \(x) 1:6 %in% x))
>> > mean(p)
>> > # [1] 0.9116667
>>
>> This should be
>>
>> yes_no <- apply(prob_frame, 1, \(x) all(1:6 %in% x))
>> p <- mean(yes_no)
>> p
>> # [1] 0.53
>>
>>
>> Rui Barradas
>>
>>
>>
>> >
>> > prob_frame <- as.data.frame(prob_frame)
>> >
>> >
>> > Hope this helps,
>> >
>> > Rui Barradas
>> >
>> >
>> > Às 05:02 de 21/04/2022, Paul Bernal escreveu:
>> >> Dear friend Bert,
>> >>
>> >> Thank you so much for your kind reply. The first thing I need to do is to
>> >> simulate dice rolls, say 120 times.
>> >>
>> >> I want to populate an m by 12 dataframe with the results of each dice
>> >> roll.
>> >> For example, the result from dice roll #1 would need to go on row 1,
>> >> column1, the result from dice roll #2 would have to go in row 1 column 2,
>> >> and so on.
>> >>
>> >> The reason why I want to store those results in a dataframe is to be able
>> >> to perform some other calculations afterwards.
>> >>
>> >> This is for a project I am doing.
>> >>
>> >> So this is the situation:
>> >> You and five friends – a total of six people – plan to meet once per
>> >> month
>> >> to have dinner together, with one of you choosing the restaurant each
>> >> month. Rather than scheduling the entire year in advance, you decide to
>> >> make it interesting: each month a single six-sided die will be rolled to
>> >> determine which of you gets to choose the restaurant that month. How
>> >> likely
>> >> is it that everyone will have a chance to eat at their own favorite
>> >> restaurant? That is, what is the probability p that over the next 12
>> >> months, each of you will have had at least one opportunity to choose
>> >> where
>> >> to eat?
>> >>
>> >> This is what I am asked to do:
>> >> Write a program to estimate the desired probability p via simulation. The
>> >> program should input a sequence of positive integer number of trials to
>> >> simulate using the language's pseudorandom number generator and calculate
>> >> the corresponding fractions of simulated trials that are “successful"
>> >> (i.e., all 6 parties get at least one opportunity to choose where to eat.
>> >> Alice, Bob, Charley, Fred, Ellen, Don, Don, Don, Don, Alice, Charley, Bob
>> >> is a successful trial. Alice, Bob, Charley, Ellen, Don, Don, Don, Don,
>> >> Ellen, Alice, Charley, Bob is not a successful trial since Fred does not
>> >> get to choose.)
>> >> Turn in a set of 10 trials showing each roll of the dice to show
>> >> correctness. Label the out-comes. Keep in mind that a single trial
>> >> requires
>> >> rolling the die twelve times. Calculate and print the average
>> >> probability p
>> >> for the set. Please refer to your friends by name.
>> >>
>> >> For this reason, I am trying to simulate the n trials, and then
>> >> populate a
>> >> table with the results from the trials. I have to simulate a dice roll
>> >> dice
>> >> for each month and for each row. Rows would be equivalent to years, and
>> >> then columns would be equivalent to the month of a particular year.
>> >>
>> >> Once I store the results in a dataframe, everything is much easier.
>> >>
>> >> I installed package dice and performed simulations by doing:
>> >> #declaring variables:
>> >> #1)dice_rolls which is the number of times the dice will be rolled
>> >> #2)num_dice which is the number of dice that will be rolled each time
>> >> #3)dice_sides which is the number of sides of the dice
>> >> #function dice will take each one of these variables as its parameter to
>> >> perform the simulation
>> >> dice_rolls = 120
>> >> num_dice = 1
>> >> dice_sides = 6
>> >>
>> >> #performing simulation
>> >> dice_simul = dice(rolls = dice_rolls, ndice = num_dice, sides =
>> >> dice_sides,
>> >> plot.it = TRUE)
>> >>
>> >> I tried the following, but did not work as expected:
>> >>
>> >> for (i in 1:nrow(dice_simul)){
>> >> for(j in 1:ncol(prob_frame)){
>> >> for(k in 1:nrow(prob_frame)){
>> >> prob_frame[k,j] = dice_simul[i,1]
>> >> }
>> >> }
>> >> }
>> >>
>> >> I apologize for the long explanation.
>> >>
>> >> Best regards,
>> >>
>> >> Paul
>> >>
>> >>
>> >> El mié, 20 abr 2022 a las 22:47, Bert Gunter (<bgunter.4...@gmail.com>)
>> >> escribió:
>> >>
>> >>> If I understand you correctly, it's simple.
>> >>> Matrices in R are vectors with a dimension attribute. By default, they
>> >>> are populated column by column. Use 'byrow = TRUE to populate by row
>> >>> instead. For example:
>> >>>
>> >>>> matrix (1:36, ncol = 12, byrow = TRUE)
>> >>> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12]
>> >>> [1,] 1 2 3 4 5 6 7 8 9 10 11 12
>> >>> [2,] 13 14 15 16 17 18 19 20 21 22 23 24
>> >>> [3,] 25 26 27 28 29 30 31 32 33 34 35 36
>> >>>
>> >>> I leave it to you to use the 'dimnames' argument of ?matrix to give
>> >>> names to the column and then subsequently convert to a data frame if
>> >>> you like.
>> >>>
>> >>> Bert Gunter
>> >>>
>> >>> "The trouble with having an open mind is that people keep coming along
>> >>> and sticking things into it."
>> >>> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
>> >>>
>> >>> On Wed, Apr 20, 2022 at 8:38 PM Paul Bernal <paulberna...@gmail.com>
>> >>> wrote:
>> >>>>
>> >>>> Dear friends,
>> >>>>
>> >>>> Hope you are doing well. I need to simulate a 1 dice roll for each
>> >>>> one of
>> >>>> the twelve months of the year and perform 100 trials, so I thought of
>> >>>> constructing a dataframe with twelve columns and 100 rows the following
>> >>> way:
>> >>>>
>> >>>> num_rows = 100
>> >>>>
>> >>>> prob_frame <- data.frame(matrix(NA, nrow = num_rows, ncol = 12))
>> >>>>
>> >>> colnames(prob_frame)<-c("January","February","March","April","May","June","July","August","September","October","November","December")
>> >>>
>> >>>>
>> >>>> Now, using the dice package, I can simulate n number of dice rolls as
>> >>>> follows:
>> >>>> #performing simulation
>> >>>> dice_simul = dice(rolls = dice_rolls, ndice = num_dice, sides =
>> >>> dice_sides,
>> >>>> plot.it = TRUE)
>> >>>>
>> >>>> What I would like to do is to populate each column and row with the
>> >>> results
>> >>>> of dice_simul.
>> >>>>
>> >>>> Let me show you the structure of dice_simul:
>> >>>>> str(dice_simul)
>> >>>> Classes ‘dice’ and 'data.frame': 100 obs. of 1 variable:
>> >>>> $ Red: int 2 2 1 2 5 4 4 6 1 4 ...
>> >>>>> dput(dice_simul)
>> >>>> structure(list(Red = c(2L, 2L, 1L, 2L, 5L, 4L, 4L, 6L, 1L, 4L,
>> >>>> 4L, 2L, 6L, 2L, 2L, 1L, 3L, 6L, 1L, 5L, 5L, 5L, 3L, 4L, 2L, 6L,
>> >>>> 4L, 6L, 6L, 2L, 1L, 2L, 2L, 6L, 4L, 2L, 3L, 5L, 6L, 6L, 4L, 5L,
>> >>>> 4L, 6L, 6L, 3L, 4L, 1L, 5L, 3L, 3L, 5L, 3L, 4L, 1L, 3L, 3L, 2L,
>> >>>> 4L, 1L, 2L, 1L, 6L, 3L, 5L, 5L, 3L, 4L, 4L, 5L, 4L, 1L, 5L, 3L,
>> >>>> 4L, 4L, 3L, 6L, 5L, 2L, 4L, 1L, 1L, 6L, 4L, 3L, 6L, 5L, 6L, 2L,
>> >>>> 6L, 1L, 6L, 6L, 4L, 3L, 4L, 2L, 1L, 5L)), class = c("dice",
>> >>>> "data.frame"
>> >>>> ), row.names = c(NA, -100L))
>> >>>>
>> >>>> For example, the first number of dice_simul should go to row 1 for
>> >>> January,
>> >>>> the second number of dice_simul should go to row 1 for February, ...
>> >>>> the
>> >>>> twelveth number of dice_simul should go to row 1 for December, the 13th
>> >>>> number should go to row 2 for january, and so on.
>> >>>>
>> >>>> This is what I tried to do but doesn´t work they way I want to:
>> >>>>
>> >>>> #1)dice_rolls which is the number of times the dice will be rolled
>> >>>> #2)num_dice which is the number of dice that will be rolled each time
>> >>>> #3)dice_sides which is the number of sides of the dice
>> >>>> #function dice will take each one of these variables as its
>> >>>> parameter to
>> >>>> perform the simulation
>> >>>> dice_rolls = 100
>> >>>> num_dice = 1
>> >>>> dice_sides = 6
>> >>>>
>> >>>> #performing simulation
>> >>>> dice_simul = dice(rolls = dice_rolls, ndice = num_dice, sides =
>> >>> dice_sides,
>> >>>> plot.it = TRUE)
>> >>>>
>> >>>> num_rows = 100
>> >>>>
>> >>>> prob_frame <- data.frame(matrix(NA, nrow = num_rows, ncol = 12))
>> >>>> colnames(prob_frame) <-
>> >>>>
>> >>> c("January","February","March","April","May","June","July","August","September","October","November","December")
>> >>>
>> >>>>
>> >>>>
>> >>>> for (j in 1:12){
>> >>>> for (i in 1:num_rows){
>> >>>> prob_frame[i,j]=dice_simul[i,1]
>> >>>> }
>> >>>> }
>> >>>> I basically want to populate the twelve months for the first row, then
>> >>> the
>> >>>> twelve months for the second row, and so on, until I get to populate
>> >>>> the
>> >>>> twelve months for the last row sequentially.
>> >>>>
>> >>>> How could I accomplish this?
>> >>>>
>> >>>> Any help and/or guidance will be greatly appreciated.
>> >>>>
>> >>>> Best regards,
>> >>>> Paul
>> >>>>
>> >>>> [[alternative HTML version deleted]]
>> >>>>
>> >>>> ______________________________________________
>> >>>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> >>>> https://urldefense.com/v3/__https://stat.ethz.ch/mailman/listinfo/r-help__;!!KwNVnqRv!GmY3d1J5JTqq58eyId3zjOPuWKBidPg_ojtvbhygQyudquxNCQkrcOT1xJfOQTFSlSxEJgiAwDPunCAbZaomfvI$
>> >>>> PLEASE do read the posting guide
>> >>> https://urldefense.com/v3/__http://www.R-project.org/posting-guide.html__;!!KwNVnqRv!GmY3d1J5JTqq58eyId3zjOPuWKBidPg_ojtvbhygQyudquxNCQkrcOT1xJfOQTFSlSxEJgiAwDPunCAb7rrtTbc$
>> >>>> and provide commented, minimal, self-contained, reproducible code.
>> >>>
>> >>
>> >> [[alternative HTML version deleted]]
>> >>
>> >> ______________________________________________
>> >> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> >> https://urldefense.com/v3/__https://stat.ethz.ch/mailman/listinfo/r-help__;!!KwNVnqRv!GmY3d1J5JTqq58eyId3zjOPuWKBidPg_ojtvbhygQyudquxNCQkrcOT1xJfOQTFSlSxEJgiAwDPunCAbZaomfvI$
>> >> PLEASE do read the posting guide
>> >> https://urldefense.com/v3/__http://www.R-project.org/posting-guide.html__;!!KwNVnqRv!GmY3d1J5JTqq58eyId3zjOPuWKBidPg_ojtvbhygQyudquxNCQkrcOT1xJfOQTFSlSxEJgiAwDPunCAb7rrtTbc$
>> >> and provide commented, minimal, self-contained, reproducible code.
>> >
>> > ______________________________________________
>> > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> > https://urldefense.com/v3/__https://stat.ethz.ch/mailman/listinfo/r-help__;!!KwNVnqRv!GmY3d1J5JTqq58eyId3zjOPuWKBidPg_ojtvbhygQyudquxNCQkrcOT1xJfOQTFSlSxEJgiAwDPunCAbZaomfvI$
>> > PLEASE do read the posting guide
>> > https://urldefense.com/v3/__http://www.R-project.org/posting-guide.html__;!!KwNVnqRv!GmY3d1J5JTqq58eyId3zjOPuWKBidPg_ojtvbhygQyudquxNCQkrcOT1xJfOQTFSlSxEJgiAwDPunCAb7rrtTbc$
>> > and provide commented, minimal, self-contained, reproducible code.
>>
>> ______________________________________________r-h...@r-project.org mailing
>> list -- To UNSUBSCRIBE and more,
>> seehttps://urldefense.com/v3/__https://stat.ethz.ch/mailman/listinfo/r-help__;!!KwNVnqRv!GmY3d1J5JTqq58eyId3zjOPuWKBidPg_ojtvbhygQyudquxNCQkrcOT1xJfOQTFSlSxEJgiAwDPunCAbZaomfvI$
>> PLEASE do read the posting guide
>> https://urldefense.com/v3/__http://www.R-project.org/posting-guide.html__;!!KwNVnqRv!GmY3d1J5JTqq58eyId3zjOPuWKBidPg_ojtvbhygQyudquxNCQkrcOT1xJfOQTFSlSxEJgiAwDPunCAb7rrtTbc$
>> and provide commented, minimal, self-contained, reproducible code.
>>
>>
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
