i experiencing difficulties estimating bma-model via glib(), due multicollinearity issues, though have specified columns use. please find details below. the data i'll using estimation via bayesian model averaging: cij <- c(357848,766940,610542,482940,527326,574398,146342,139950,227229,67948, 352118,884021,933894,1183289,445745,320996,527804,266172,425046, 290507,1001799,926219,1016654,750816,146923,495992,280405, 310608,1108250,776189,1562400,272482,352053,206286, 443160,693190,991983,769488,504851,470639, 396132,937085,847498,805037,705960, 440832,847631,1131398,1063269, 359480,1061648,1443370, 376686,986608, 344014) n <- length(cij); tt <- trunc(sqrt(2*n)) <- rep(1:tt,tt:1); #row numbers: year of origin j <- sequence(tt:1) #col numbers: year of development k <- i+j-1 #diagonal numbers: year of payment #since k=i+j-1, have leave out dummy in order avoid multicollinearity k <- ifelse(k == 2, 1, k) i want evaluate effect of i , j both via...