The following code, when queried with cpquery gives wildly varying results. It only does this for the case when info == “False”, all other cases give expected results. Further, removing the Boolean & from the cpquery just to leave info == “False” returns varying results. Any thoughts?

This question was migrated from Cross Validated because it can be answered on Stack Overflow. Migrated 2 hours ago. I am working inside a loop where I will need to replicate a character string a certain number of times. As I progress through the loop, the amount of times it is replicated needs to increase, […]

This question was migrated from Cross Validated because it can be answered on Stack Overflow. Migrated 2 hours ago. I am working inside a loop where I will need to replicate a character string a certain number of times. As I progress through the loop, the amount of times it is replicated needs to increase, […]

This question was migrated from Cross Validated because it can be answered on Stack Overflow. Migrated 2 hours ago. I am working inside a loop where I will need to replicate a character string a certain number of times. As I progress through the loop, the amount of times it is replicated needs to increase, […]

This question was migrated from Cross Validated because it can be answered on Stack Overflow. Migrated 2 hours ago. I am working inside a loop where I will need to replicate a character string a certain number of times. As I progress through the loop, the amount of times it is replicated needs to increase, […]

$begingroup$ This question was migrated from Stack Overflow because it can be answered on Cross Validated. Migrated 14 mins ago. For IID (independent and identically distributed) Bernoulli random numbers, we can simply run, say in R, as ### IID: xi ~ b(1,p), i=1,2,…,n ### try: simply p=1/2 ; or p=e/Π≈0.865256 # n=100000; set.seed(0); p=1/2; x=rbinom(n,size=1,prob=p); […]

$begingroup$ This question was migrated from Stack Overflow because it can be answered on Cross Validated. Migrated 14 mins ago. For IID (independent and identically distributed) Bernoulli random numbers, we can simply run, say in R, as ### IID: xi ~ b(1,p), i=1,2,…,n ### try: simply p=1/2 ; or p=e/Π≈0.865256 # n=100000; set.seed(0); p=1/2; x=rbinom(n,size=1,prob=p); […]

$begingroup$ This question was migrated from Stack Overflow because it can be answered on Cross Validated. Migrated 13 mins ago. For IID (independent and identically distributed) Bernoulli random numbers, we can simply run, say in R, as ### IID: xi ~ b(1,p), i=1,2,…,n ### try: simply p=1/2 ; or p=e/Π≈0.865256 # n=100000; set.seed(0); p=1/2; x=rbinom(n,size=1,prob=p); […]

$begingroup$ This question was migrated from Stack Overflow because it can be answered on Cross Validated. Migrated 13 mins ago. For IID (independent and identically distributed) Bernoulli random numbers, we can simply run, say in R, as ### IID: xi ~ b(1,p), i=1,2,…,n ### try: simply p=1/2 ; or p=e/Π≈0.865256 # n=100000; set.seed(0); p=1/2; x=rbinom(n,size=1,prob=p); […]

$begingroup$ This question was migrated from Stack Overflow because it can be answered on Cross Validated. Migrated 13 mins ago. For IID (independent and identically distributed) Bernoulli random numbers, we can simply run, say in R, as ### IID: xi ~ b(1,p), i=1,2,…,n ### try: simply p=1/2 ; or p=e/Π≈0.865256 # n=100000; set.seed(0); p=1/2; x=rbinom(n,size=1,prob=p); […]