probability

问题 I am using fdc of hydroTSM package . I have three data.frame and i would like to construct Flow duration curves (FDC) of the data.frame using facet_wrap functionality of ggplot to have the plots in three rows and one column . the following will produce FDC curves for DF1 . library(tidyverse) library(hydroTSM) library(gridExtra) DF1 = data.frame(Ob = runif(1000,0,500), A = runif(1000,0,700), B = runif(1000,2,800)) DF2 = data.frame(Ob = runif(1000,0,500), A = runif(1000,0,700), B = runif(1000,2

问题 I am using fdc of hydroTSM package . I have three data.frame and i would like to construct Flow duration curves (FDC) of the data.frame using facet_wrap functionality of ggplot to have the plots in three rows and one column . the following will produce FDC curves for DF1 . library(tidyverse) library(hydroTSM) library(gridExtra) DF1 = data.frame(Ob = runif(1000,0,500), A = runif(1000,0,700), B = runif(1000,2,800)) DF2 = data.frame(Ob = runif(1000,0,500), A = runif(1000,0,700), B = runif(1000,2

问题 For instance, this is 5 choose 2: var array = [0,1,2,3,4]; var result = array.flatMap( (v, i) => array.slice(i+1).map(w => [v, w]) ); console.log(result); How would I be able to do 5 choose 3 using this method? 回答1: Just add another level of nesting: var array = [0,1,2,3,4]; var result = array.flatMap((v, i) => array.slice(i+1).flatMap((w, j) => array.slice(i+1+j+1).map(u => [v, w, u] ) ) ); console.log(result); At this point, it might be easier to do with recursion though: function choose

问题 I am currently using xarray to make probability maps. I want to use a statistical assessment like a “counting” exercise. Meaning, for all data points in NEU count how many times both variables jointly exceed their threshold. That means 1th percentile of the precipitation data and 99th percentile of temperature data. Then the probability (P) of join occurrence is simply the number of joint exceedances divided by the number of data points in your dataset. <xarray.Dataset> Dimensions: (latitude:

问题 I am currently using xarray to make probability maps. I want to use a statistical assessment like a “counting” exercise. Meaning, for all data points in NEU count how many times both variables jointly exceed their threshold. That means 1th percentile of the precipitation data and 99th percentile of temperature data. Then the probability (P) of join occurrence is simply the number of joint exceedances divided by the number of data points in your dataset. <xarray.Dataset> Dimensions: (latitude:

问题 Could someone generate those graphs or at least help me with that ? I want to generate that probability of getting heads and tails in a undetermined number of flips. Actually its not like that but consider pthetaGivenData like this and check my code. Probably you´ll know what I want to get. This is what I´ve done so far: The while wasnt working. I couldnt store my results of each coin result in add, so then, pthetaGivenData in storage as well. I was trying to generate the first five data

问题 Could someone generate those graphs or at least help me with that ? I want to generate that probability of getting heads and tails in a undetermined number of flips. Actually its not like that but consider pthetaGivenData like this and check my code. Probably you´ll know what I want to get. This is what I´ve done so far: The while wasnt working. I couldnt store my results of each coin result in add, so then, pthetaGivenData in storage as well. I was trying to generate the first five data

问题 I have code that generates a certain value from -10 to 10 given a range from [0,1) The code takes the value from -10 to 10 and it will append it to a list, according to its probability. For example, -10 would be put in the list 0 times since it corresponds to the value 0, and 10 would be put 100 times (as a normalization) since it corresponds to 1 in the range. Here is the code: #!/usr/bin/env python import math import numpy as np import matplotlib.pyplot as plt pos = [] ceilingValue = 0.82

问题 I have code that generates a certain value from -10 to 10 given a range from [0,1) The code takes the value from -10 to 10 and it will append it to a list, according to its probability. For example, -10 would be put in the list 0 times since it corresponds to the value 0, and 10 would be put 100 times (as a normalization) since it corresponds to 1 in the range. Here is the code: #!/usr/bin/env python import math import numpy as np import matplotlib.pyplot as plt pos = [] ceilingValue = 0.82

问题 For a task I am to use ConditionalProbDist using LidstoneProbDist as the estimator, adding +0.01 to the sample count for each bin. I thought the following line of code would achieve this, but it produces a value error fd = nltk.ConditionalProbDist(fd,nltk.probability.LidstoneProbDist,0.01) I'm not sure how to format the arguments within ConditionalProbDist and haven't had much luck in finding out how to do so via python's help feature or google, so if anyone could set me right, it would be