regresiion

  1. M

    Too many dummy variables in Regression

    we have about 50000 models of mobile phone (like Galaxy S7, iPhone 9) in database and the size of data is about 3 million. We want to find the mobile phones that have the least call success rate ( the numbers of successful call divided by total call). We want to run a Regression model to find...
  2. S

    AIC computation

    (1) Compute the Akaike Information Criterion (AIC) value for the linear regression model Y = b0 + b1*X1 + b2*X2 + b3*X3. The regression model was fitted on a sample of 250 observations and yielded a likelihood value of 0.18. (a) 9.49 (b) 11.43 (c) 25.52 (d) 15.55 (2)...
  3. A

    Logistic regression and significance of continuous variables across 3 periods

    I'm currently working on a logistic regression analysis in R with a binary response variable (0 = non-used; 1 = used location). I am modeling non-random habitat selection for a species of wildlife. I recently ran into an issue where I need to evaluate non-random habitat selection across 3...
  4. R

    Durbin-Watson statistic below 2, fixed effect model

    Hello I am asking for your advice. I am working with unbalanced panel data set. Sample contains data about 11 largest Finnish insurance companies, time period is 13 years. Dependent variable is profitability indicator ratio; independent variables are concentration measured by HHI index and...