Article Categories
- All Categories
-
Data Structure
-
Networking
-
RDBMS
-
Operating System
-
Java
-
MS Excel
-
iOS
-
HTML
-
CSS
-
Android
-
Python
-
C Programming
-
C++
-
C#
-
MongoDB
-
MySQL
-
Javascript
-
PHP
-
Economics & Finance
Programming Articles
Page 1263 of 2547
How to generate Bernoulli random variable in R?
Each value in Bernoulli random variable represents success or a failure for a single trial that makes it different from Binomial random variable because a Binomial random variable represents number of success or failure for a number of trials. To generate a Bernoulli random variable, we can use rbinom function but we need to pass 1 for size argument.Examplerbinom(120,1,0.71)Output[1] 1 1 1 1 1 1 0 0 0 1 1 1 1 1 1 1 1 1 1 0 0 0 1 1 1 0 0 0 1 1 1 1 1 1 1 0 1 [38] 1 0 1 1 1 0 0 1 0 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 0 [75] 1 1 0 1 1 1 1 1 0 0 1 0 1 1 1 0 1 1 1 1 1 1 0 1 1 1 0 1 1 0 1 1 1 1 1 1 0 [112] 0 0 1 1 0 1 1 1 1Examplerbinom(120,1,0.1)Output[1] 0 0 0 0 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 1 1 0 [38] 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [75] 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [112] 0 0 0 0 0 0 0 0 0Examplerbinom(120,1,0.91)Output[1] 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [38] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [75] 1 1 0 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 0 1 0 1 1 1 1 1 1 1 1 1 1 1 [112] 1 1 1 1 1 1 1 1 1Examplerbinom(120,1,0.999)Output[1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [38] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [75] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [112] 1 1 1 1 1 1 1 1 1Examplerbinom(120,1,0.099)Output[1] 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [38] 1 0 0 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 [75] 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 [112] 0 0 0 0 0 0 0 0 0Examplerbinom(200,1,0.50)Output[1] 1 1 1 0 1 1 0 1 0 1 1 0 1 0 0 0 0 1 1 1 0 1 1 0 0 0 1 0 1 1 1 1 0 0 1 1 0 [38] 1 1 0 0 1 1 1 1 0 0 1 0 0 1 1 1 1 1 0 1 0 0 0 1 1 0 0 0 1 1 0 1 0 1 1 1 1 [75] 0 1 1 1 1 1 0 1 0 1 1 1 0 0 0 1 1 0 1 0 0 1 0 0 1 1 1 1 0 1 0 1 0 0 0 0 0 [112] 0 0 0 1 1 0 1 0 0 1 1 1 1 1 1 0 1 0 1 1 0 0 1 1 1 0 0 1 1 1 0 0 1 1 1 0 0 [149] 1 0 1 1 0 0 1 1 0 0 0 1 1 1 1 0 0 1 0 1 1 1 0 0 0 0 1 1 0 1 0 1 0 1 1 0 0 [186] 1 1 1 0 1 1 0 0 0 1 1 1 0 1 1Examplerbinom(200,1,0.51)Output[1] 1 1 1 1 0 0 0 1 0 0 1 0 1 0 1 1 0 0 1 1 0 1 0 1 1 1 0 1 0 0 1 1 0 0 0 1 1 [38] 1 1 1 1 0 1 1 1 1 1 1 1 0 0 1 0 1 0 0 1 1 0 0 0 1 0 0 1 0 1 1 1 0 0 1 1 0 [75] 0 1 1 0 0 1 0 0 0 1 0 1 0 1 1 0 1 1 0 1 0 0 0 1 0 1 1 1 0 1 0 0 1 1 1 1 0 [112] 1 1 1 0 0 0 0 0 0 1 0 0 0 1 1 0 1 1 0 1 0 1 1 1 1 1 0 0 0 1 0 1 0 0 0 0 0 [149] 1 1 0 0 0 1 1 0 1 0 0 0 1 1 0 0 0 0 1 1 1 0 1 0 0 1 0 1 0 0 1 1 1 0 1 1 0 [186] 0 1 0 1 1 0 0 1 1 1 1 0 1 1 0Examplerbinom(200,1,0.75)Output[1] 1 0 0 0 1 1 0 1 0 1 1 0 1 1 1 1 1 1 1 0 1 1 0 1 1 1 1 1 1 1 0 1 0 0 1 1 1 [38] 1 0 0 1 1 0 1 1 0 1 1 1 1 1 0 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 [75] 1 0 1 1 0 1 1 1 0 1 1 1 1 1 0 0 1 1 1 1 1 1 1 0 1 1 1 1 0 1 0 1 1 1 1 1 0 [112] 1 1 1 0 0 1 1 0 1 1 0 1 0 1 1 1 0 1 0 1 1 1 0 1 1 1 1 1 1 0 1 1 1 1 1 1 0 [149] 1 1 1 1 1 1 0 1 1 0 0 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 0 1 1 1 1 1 0 1 1 1 1 [186] 1 1 1 1 1 0 0 0 1 1 1 0 1 1 1Examplerbinom(200,1,0.89)Output[1] 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 [38] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 0 1 0 1 1 1 1 1 1 0 1 1 1 1 1 [75] 1 1 1 1 1 1 1 1 1 0 1 1 1 0 0 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 [112] 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 0 1 1 1 0 1 1 1 1 1 1 1 1 0 0 1 0 1 1 [149] 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 0 0 1 1 1 1 1 1 1 1 1 1 1 [186] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1Examplerbinom(200,1,0.05)Output[1] 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [38] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [75] 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [112] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [149] 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 [186] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0Examplerbinom(200,1,0.15)Output[1] 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 [38] 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 [75] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [112] 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0 0 0 0 0 0 [149] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 0 0 [186] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0Examplerbinom(200,1,0.20)Output[1] 1 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0 0 [38] 0 0 1 1 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 1 0 0 0 0 0 1 0 0 0 0 1 0 1 [75] 0 0 1 0 0 0 0 1 0 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 [112] 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 1 0 1 0 0 0 1 1 0 0 0 1 0 1 1 0 0 0 0 0 1 [149] 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 1 0 0 1 0 0 0 1 0 0 0 [186] 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0Examplerbinom(200,1,0.25)Output[1] 0 1 1 0 0 0 1 1 0 0 1 1 0 0 0 0 1 0 1 0 0 0 1 0 0 0 0 1 0 0 0 1 1 0 0 0 0 [38] 0 1 0 0 0 0 0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [75] 1 0 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 1 0 0 0 1 [112] 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 [149] 0 0 0 0 1 0 0 0 0 1 0 1 0 0 0 1 0 0 0 1 1 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 [186] 0 1 1 0 0 0 0 0 0 1 0 0 0 0 1Examplerbinom(200,1,0.35)Output[1] 0 1 0 0 0 0 1 0 0 1 0 1 0 0 0 1 1 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 [38] 1 0 1 1 0 0 1 0 0 1 1 1 0 1 1 0 1 1 0 0 0 0 0 0 0 0 1 0 1 0 1 0 1 0 0 1 1 [75] 1 1 0 0 0 1 0 0 1 0 0 0 0 0 1 0 1 0 1 1 0 0 1 1 1 0 0 0 0 1 0 0 1 0 1 0 0 [112] 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 1 1 0 1 1 1 1 0 0 1 0 1 1 0 0 0 0 1 1 [149] 1 0 0 1 1 0 1 0 0 0 1 1 0 1 1 0 1 0 1 1 0 0 0 0 0 0 1 0 0 1 0 1 0 1 0 0 0 [186] 0 1 0 0 0 1 0 0 1 1 0 1 0 0 0
Read MoreHow to make all the elements in a list of equal size in R?
We know that a list can multiple elements of different types as well as of different size. For example, a list that contains two elements then one element may contain fifteen elements and the other might have twenty-five elements. In this situation, we might want to fill the first element with ten more elements so that the size of both the elements become equal. This can be done by using lapply function as shown in the below examples.Consider the below list −Exampleset.seed(101) x1
Read MoreHow to remove rows from data frame in R based on grouping value of a particular column?
If we have a grouping column in an R data frame and we believe that one of the group values is not useful for our analysis then we might want to remove all the rows that contains that value and proceed with the analysis, also it might be possible that the one of the values are repeated and we want to get rid of that. In this situation, we can do subsetting of the data frame using negation and single square brackets.Exampleset.seed(1212) x
Read MoreHow to remove everything before values starting after underscore from column values of an R data frame?
If a column in an R data frame contain string values that are separated with an underscore and stretches the size of the column values that also contain common values then it would be wise to remove underscore sign from all the values at once along with the values that is common. This will help us to read the data properly as well as analysis will become easy. For this purpose, we can use gsub functionConsider the below data frame −Exampleset.seed(191) ID
Read MoreHow to perform fisher test in R?
The fisher test helps us to understand whether there exists a significant non-random relationship among categorical variables or not. It is applied on contingency tables because these tables are used to represent the frequency for categorical variables and we can apply it on a matrix as well as matrices have the similar form. In R, we can use fisher.test function to perform the fisher test.ExampleM1
Read MoreParent and Child classes having same data member in Java
The parent class can hold reference to both the parent and child objects. If a parent class variable holds reference of the child class, and the value is present in both the classes, in general, the reference belongs to the parent class variable. This is due to the run-time polymorphism characteristic in Java.ExampleFollowing is an example −class Demo_base { int value = 1000; Demo_base() { System.out.println("This is the base class constructor"); } } class Demo_inherits extends Demo_base { int value = 10; Demo_inherits() { System.out.println("This is the inherited class ...
Read MoreQuantifiers in Java
Quantifier is a concept that allows the programmer to specify the number of occurrences of a specific type of value in the regular expression. There are different types of quantifiers, some of them include ‘?’ (Reluctant quantifier), ‘+’ (Possessive quantifier). In this post, we will see how reluctant quantifier works.ExampleFollowing is an example −import java.util.regex.Matcher; import java.util.regex.Pattern; public class Demo { public static void main(String[] args) { Pattern my_pattern = Pattern.compile("sam+?"); Matcher my_match = my_pattern.matcher("samp"); while (my_match.find()) System.out.println("The pattern has been found - " + my_match.start() + ...
Read MoreRetrieving Elements from Collection in Java- For-each loop
The ‘for-each’ loop is used to iterate over a set of elements that is stored in a data structure.Syntaxfor (element e: collection) { System.out.println(e); }ExampleFollowing is an example −public class Demo { public static void main(String[] args) { int[] my_vals = {5, 67, 89, 31, -1, 2, 0}; int sum = 0; for (int number: my_vals) { sum += number; } System.out.println("The sum is " + sum); } }OutputThe sum is 193A class named Demo contains the main ...
Read MoreHow to find the groupwise mean and save it in a data frame object in R?
We often need groupwise mean in data analysis, especially in situations where analysis of variance techniques is used because these techniques helps us to compare different groups based on their measures of central tendencies and measures of variations. It can be done by using aggregate function so that the output can be saved in a data frame object. In the below examples, we can see how it can be done and also check the final object type.ExampleConsider the below data frame −set.seed(109) Salary
Read MoreRetrieving Elements from Collection in Java- Iterator
Following is an example to retrieve elements −Exampleimport java.util.*; public class Demo { public static void main(String args[]) { HashSet my_hs = new HashSet() ; my_hs.add("Joe"); my_hs.add ("Rob"); Iterator my_it = my_hs.iterator(); System.out.println("The elements are : "); while (my_it.hasNext()) System.out.println(my_it.next()); } }OutputThe elements are : Joe RobA class named Demo contains the main function, which defines a HashSet collection. Elements are added to this collection using the ‘add’ function. An iterator is defined, and the elements ...
Read More