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- Write a function that takes a vector of integers, an integer n representing the number of elements in that vector, and an integer b. Implement the sequential search algorithm to look for the integer b in the vector. The sequential search works as follows: you must look at all the elements of the vector until you find the b, from the first to the last. The function must return an integer representing how many elements the function tested until it found b. If it does not find the function, it must return 0. The name of the function must be called "busca_seq". Program in C.1. Write a function (call it mylm) that takes two inputs: a vector y of n elements and a matrix X of n times k elements, where n should be greater than k, and returns three outputs: bhat = solve(X'X)X'y, X'X and X'y (the prime symbol means transpose). Use the attr method to return the second and third outputs. Note that you do not need to specify values for y and X when you write this function.Create a MATLAB function that selects a random element from a list of values in a vector. Using the built-in function 'randi'. Example: For input options = [3, 2, 5], the output for this function should be able to choose one of the three numbers, with an equal chance of choosing each (20% chance each). chosen_value = select_random_option([3, 2, 5]) value = 3 chosen_value = select_random_option([3, 2, 5]) value = 5 chosen_value = select_random_option([3, 2, 5]) value = 2
- Run my function on {(1,4),(0,6),(3,5),(2,9),(7,8)}. Is the output what you expect? Find the problem and fix it, writing a correct version of the function. Again, use the same function name, i.e., count_crossings_and_nestings. Demonstrate that the new version works by testing it on the example provided. Now write a well-documented version of your function count_crossings_and_nestings. Add a document string and plenty of comments.Write a Python function that takes in three parameters - an adjacency matrix of a simple directed graph, a start node, and an end node; and returns "True" if there is a way to get from the start node to the end node using the provided edges. You can use this file as a starter code: path.py ↓ For example: Using the same graph given above. Consider your function with the same adjacency matrix given above as input and: If the start node is 1 and the end node is 4 then your function should return True. If the start node is 2 and the end node is 4 then your function should return False. Input: This function will have three parameters. First is an adjacency matrix in the form of a list of lists (as given above). Then the start_node and the end_node will be integers. Note that python indexing starts from 0 and not from 1, so the naming of the nodes will also follow the python convention and start from 0 instead of 1. Output: Boolean value: True or False.Write a MATLAB function (testLucky.m) that takes a number as an input argument and checks to see if the number is lucky. In the function, begin by defining a vector named secretLucky with the values 19, 22, 5, 9, 11, 15, 21. These are secret lucky numbers. Use a for-loop in the function to check, element-by-element, if the number passed in to the function is in the secretLucky vector. If the number is found in secretLucky, return true (1). If the number is not found in secretLucky, return false (0). Include help comments in the function. Your testLucky function must behave as shown below: (user input is underlined) » help testlucky testlucky(x) - determine whether x is a lucky number return true (1) if x is a lucky number return false (0) if x is not a lucky number Author: your_name » testlucky(5) ans = logical » testlucky(6) ans - logical Hint: To get a logical 1 and logical 0 as output of your function, see "help true" and "help false".
- The following table contains output from a lasso fit to a linear model with d= 5 variables and n = 65 observations. Starting from the left, the columns are X, and B₁, ..., B5, i.e. each row has X and the transposed column vector B¹(X). 0.00000 0.00000 -0.04596 0.08497 0.04129 -0.08195 -0.00764 0.22778 -0.04274 0.07868 0.03430 -0.07599 0.00000 1.96117 -0.02092 0.04606 0.00000 -0.04090 3.28220 0.00000 0.02263 0.00000 -0.02105 4.49485 0.00000 0.00375 0.00000 0.00000 4.73846 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 You will perform computations using this table and report your results. A) Compute the maximum value of the L₁ norm for vectors of coefficients attained in this table, that is compute maxx ||3¹(A)||₁ B) Consider the 2nd breakpoint from the top of the table, namely the breakpoint corresponding to A-0.22778. Compute the L₁ norm for the vector of coefficients at this point in the path, i.e. compute || (0.22778)||1 C) For the same 2nd breakpoint in the table, compute…The world population data spans from 1960 to 2017. We'd like to build a predictive model that can give us the best guess at what the future or past population of a particular country was or might be. First, however, we need to formulate our data such that sklearn's Ridge regression class can train on our data. To do this, we will write a function that takes as input a country name and return a 2-d numpy array that contains the year and the measured population. Function Specifications: Should take a str as input and return a numpy array type as output. The array should only have two columns containing the year and the population, in other words, it should have a shape (?, 2) where ? is the length of the data. The values within the array should be of type int. Hint: You'll need to use both the the population and country map dataframes given above. ### START FUNCTIONdef get_year_pop(country_name): # your code here returnThis assignment is to a analyze a random experiment. Assume that you have to toss a fair coin (50% probability for each head and tail) N times, where N→ 00, When head comes up, you will be rewarded (gain) RM1, while if tail comes up, you will be penalized (loss) RM1. Write a function function sum_return coin_toss (N) that returns a row vector sum_return of length N+1. Each column i represents gained sum from i-1 number of coin tosses, i.e. sum_return (1) =0. To solve this problem, you will need both a for statement and the rand function. Try out several (minimum of 2) tries a value of N of 1000, 10000, 100000, 1000000 and plot the results. The x-axis must show the values from 0 to N. The y-axis should be limited to the maximum gain and minimum loss during each experiment. Note that as N is large, plotting N points will take a long time. Find a way on how this can be made faster.
- Write a program that reads a list of words. Then, the program outputs those words and their frequencies. The input begins with an integer indicating the number of words that follow. Ex: If the input is: 5 hey hi Mark hi mark the output is: hey 1 hi 2 Mark 1 hi 2 mark 1 Hint: Use two vectors, one for the strings, another for the frequencies. Your program must define and use the following function:int GetFrequencyOfWord(vector<string> wordsList, string currWord) #include <iostream>#include <vector> #include <string>using namespace std; /* Define your function here */ int main() {/* Type your code here */ return 0;} Please help me with this problem using c++.Write a program that reads a list of words. Then, the program outputs those words and their frequencies. The input begins with an integer indicating the number of words that follow. Ex: If the input is: 5 hey hi Mark hi mark the output is: hey 1 hi 2 Mark 1 hi 2 mark 1 Hint: Use two vectors, one for the strings, another for the frequencies. Your program must define and use the following function: int GetFrequencyOfWord(vector<string> wordsList, string currWord)Write a program that prompts the user to enter an integer m and find the smallest integer n such that m * n is a perfect square. (Hint: Store all smallest factors of m into a vector. n is the product of the factors that appear an odd number of times in the vector. For example, consider m = 90, store the factors 2, 3, 3, 5 in a vector. 2 and 5 appear an odd number of times in the vector. So, n is 10.)