Using the chicago dataset from the faraway package fit a Tweedie GLM similar to our notes, but this time only use the age, theft and $log($income$)$ as predictors. Report your value for $p$ and $.$ For the last observation, zip code $60645,$ make a predictive density plot. Then fit a full model like the one in our notes $($with predictors race, fire, theft, age, and income$)),$ and plot the predictive density plot for the last observation, zip code $60645.$ Comment on the differences in your two models. Need the code for R$!$ Thanks

$\backslash$table$[[,$race ${?}^{**},$fire,theft $=,$age,volact,involact,income$],[60626,10\mathrm{.}0,6\mathrm{.}2,29,60\mathrm{.}4,5\mathrm{.}3,0\mathrm{.}0,11744],[60640,22\mathrm{.}2,9\mathrm{.}5,44,76\mathrm{.}5,3\mathrm{.}1,0\mathrm{.}1,9323],[60613,19\mathrm{.}6,10\mathrm{.}5,36,73\mathrm{.}5,4\mathrm{.}8,1\mathrm{.}2,9948],[60657,17\mathrm{.}3,7\mathrm{.}7,37,66\mathrm{.}9,5\mathrm{.}7,0\mathrm{.}5,10656],[60614,24\mathrm{.}5,8\mathrm{.}6,53,81\mathrm{.}4,5\mathrm{.}9,0\mathrm{.}7,9730],[60610,54\mathrm{.}0,34\mathrm{.}1,68,52\mathrm{.}6,4\mathrm{.}0,0\mathrm{.}3,8231],[60611,4\mathrm{.}9,11\mathrm{.}0,75,42\mathrm{.}6,7\mathrm{.}9,0\mathrm{.}0,21480],[60625,7\mathrm{.}1,6\mathrm{.}9,18,78\mathrm{.}5,6\mathrm{.}9,0\mathrm{.}0,11104],[60618,5\mathrm{.}3,7\mathrm{.}3,31,90\mathrm{.}1,7\mathrm{.}6,0\mathrm{.}4,10694],[60647,21\mathrm{.}5,15\mathrm{.}1,25,89\mathrm{.}8,3\mathrm{.}1,1\mathrm{.}1,9631],[60622,43\mathrm{.}1,29\mathrm{.}1,34,82\mathrm{.}7,1\mathrm{.}3,1\mathrm{.}9,7995],[60631,1\mathrm{.}1,2\mathrm{.}2,14,40\mathrm{.}2,14\mathrm{.}3,0\mathrm{.}0,13722],[60646,1\mathrm{.}0,5\mathrm{.}7,11,27\mathrm{.}9,12\mathrm{.}1,0\mathrm{.}0,16250],[60656,1\mathrm{.}7,2\mathrm{.}0,11,7\mathrm{.}7,10\mathrm{.}9,0\mathrm{.}0,13686],[60630,1\mathrm{.}6,2\mathrm{.}5,22,63\mathrm{.}8,10\mathrm{.}7,0\mathrm{.}0,12405],[60634,1\mathrm{.}5,3\mathrm{.}0,17,51\mathrm{.}2,13\mathrm{.}8,0\mathrm{.}0,12198],[60641,1\mathrm{.}8,5\mathrm{.}4,27,85\mathrm{.}1,8\mathrm{.}9,0\mathrm{.}0,11600],[60635,1\mathrm{.}0,2\mathrm{.}2,9,44\mathrm{.}4,11\mathrm{.}5,0\mathrm{.}0,12765],[60639,2\mathrm{.}5,7\mathrm{.}2,29,84\mathrm{.}2,8\mathrm{.}5,0\mathrm{.}2,11084],[60651,13\mathrm{.}4,15\mathrm{.}1,30,89\mathrm{.}8,5\mathrm{.}2,0\mathrm{.}8,10510],[60644,59\mathrm{.}8,16\mathrm{.}5,40,72\mathrm{.}7,2\mathrm{.}7,0\mathrm{.}8,9784],[60624,94\mathrm{.}4,18\mathrm{.}4,32,72\mathrm{.}9,1\mathrm{.}2,1\mathrm{.}8,7342],[60612,86\mathrm{.}2,36\mathrm{.}2,41,63\mathrm{.}1,0\mathrm{.}8,1\mathrm{.}8,6565],[60607,50\mathrm{.}2,39\mathrm{.}7,147,83\mathrm{.}0,5\mathrm{.}2,0\mathrm{.}9,7459],[60623,74\mathrm{.}2,18\mathrm{.}5,22,78\mathrm{.}3,1\mathrm{.}8,1\mathrm{.}9,8014],[60608,55\mathrm{.}5,23\mathrm{.}3,29,79\mathrm{.}0,2\mathrm{.}1,1\mathrm{.}5,8177]]$

$\backslash$table$[[.,$race,fire,theft,age,volact,involact,income