Q6. You model a loss process using a lognormal distribution with parameters and o. You aregiven:(i) The maximum likelihood estimates of u and o are μ = 4.215 and ☎ = 1.093.(0.1(iii) The mean of the lognormal distribution is exp (u +).(ii) The estimated covariance matrix of û and ☎ is0.1195 00.05970Estimate the variance of the maximum likelihood estimate of the mean of the lognormaldistribution, using the delta method.

From the given information, The maximum likelihood estimates of μ and σ are μ^=4.215 and σ^=1.093.…

Answered: You model a loss process using a…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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In a study in pre-term infants, a group where breast feeding is difficult because the mother gets home before the baby does, you run a logistic regression model where the independent variable is the mother's age and the dependent variable is whether the infant was breast feeding at discharge from the hospital. If the log odds for breast feeding for a 20 year old mom was -3.654 + (20) * 0.157 = -0.514, compute the predicted probability for breast feeding for a 20 year old mom. 0.598 / (1+0.598) O 0.598 0.598 / (1 - 0.598) -0.514 / (1+0.598)
Suppose that we want to build a model that predicts the group membership of a hurricane, either tropical (0) or non-tropical (1) based on the latitude of formation of the huricane. The response variable is the binary variable Type.new (type of hurricane) and the predictor variable is FirstLat (First Latitude). Using R, we build a model by applying the glm () function. For the logistic regression model, we specify family = "binomial". The data is available at https://userpage.fu-berlin.de/soga/200/2010 data sets hurricanes.xlsx. The R code is #set up filename my.filename 1z|) <2e-16 *** 0.96148 -9.446 0.37283 0.03947 9.447 <2e-16 *** --- *# Signif. codes: 0 '*** 0.001 **' 0.01 '*' 0.05'.' 0.1 '' 1 # (Dispersion parameter for binomial family taken to be 1) Null deviance: 463.11 on 336 degrees of freedom *# Residual deviance: 232.03 on 335 degrees of freedom *# AIC: 236.03 *# Number of Fisher Scoring iterations: 6 What is the interpretation of the p-value of the predictor variable…
4. When the Titanic sank in 1912, there were over 1,300 passengers aboard. A random sample of 50 passengers that were aboard is taken. The amount they paid for the voyage and whether or not they survived is recorded. A model is fit to predict the probability they survived when the ship sank is obtained. Survived Logistic Fit of Survived By Fare 1.00 0.75 0.50- 0.25- 50 4 Parameter Estimates 100 Term Intercept -1.404254 0.4353289 Fare 0.01246686 0.0097945 For log odds of Yes/No Fare Estimate Std Error ChiSquare 10.41 1.62 150 200 Prob> ChiSq 0.0013 0.2031 No Yes a) Suppose someone paid a fare of 25 pounds. Predict the probability they survived. b) How much would someone pay to have at least a 65% chance of survival?
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You model a loss process using a lognormal distribution with parameters and o. You a given: (i) The maximum likelihood estimates of u and o are = 4.215 and 6 = 1.093. 0.1195 0 (ii) The estimated covariance matrix of û and ☎ is 0.050