r - 估计与观察到的泊松分布和二项分布之间的比较不会产生足够的结果

Question

# Packages
library(MASS)# Pacote MASS
library(car) # Pacote car


# Create some artificial numbers with binomial negative distribution
S<-10
P<-0.6
N<-rnbinom(n=283, size=S, prob=P)

# Poisson --------------------------------------------------------------------------------------
(poisson <- fitdistr(N,"poisson"))

# Comparation between observed vs estimated values 
(n <- length(N))
est1 <-n*dpois(N, lambda=poisson$estimate)  ## Estimate the values 
fecdf1 <- ecdf(N) ### Empirical Cumulative Distribution Function
knotsX1 <- knots(fecdf1) # Aggregate in classes
emp1 <- fecdf1(c(knotsX1,Inf))  # frequency for each value in the distribution
chisq.test(table(emp1),table(est1))

Pearson 的卡方检验数据：table(emp1) 和 table(est1) X-squared = 8.9722, df = 12, p-value = 0.7053

# Negative binomial ----------------------------------------------------------------------------
( bn <- fitdistr(N,"negative binomial"))

# Comparation between observed vs estimated values 
par <- bn$estimate
(size <- par[1])#k
(mu <- par[2])#Media
(n <- length(N))
est2 <-n*dnbinom(N,size=size,mu=mu)  ## Estimate the values 
fecdf2 <- ecdf(N)  ### Empirical distribution function
knotsX2 <- knots(fecdf2) # Aggregate in classes
emp2 <- fecdf2(c(knotsX2,Inf))  # frequency for each value in the distribution
chisq.test(table(emp2),table(est2)) 

Pearson 的卡方检验数据：table(emp2) 和 table(est2) X-squared = 8.9722, df = 12, p-value = 0.7053

是否有一些解释为什么我在泊松和二项式负分布之间的卡方检验（重复多次）中具有完全相同的 p 值？我预计负二项式分布超过 0.05，泊松分布 <0.05，但这不会发生。