R/segConstr.lm.fit.r

In segmented: Regression Models with Break-Points / Change-Points Estimation (with Possibly Random Effects)

segConstr.lm.fit <-function (y, XREG, Z, PSI, w, offs, opz, return.all.sol = FALSE) 
{
    useExp.k = TRUE
    search.minWO<-function(h, psi, psi.old, X, y, w, offs) {
        psi.ok<- psi*h + psi.old*(1-h)
        PSI <- matrix(psi.ok, n, ncol = length(psi.ok), byrow=TRUE)
        U1 <- (Z - PSI) * (Z > PSI)
        
        for(i in 1:length(RList)){#trasforma le U
          UList[[i]]<- cbind(Zseg[,i], U1[, id.psi.group==i])%*%invA.RList[[i]] #
          #nomiUList[[i]]<- rep(i, ncol(UList[[i]]) )
        }
        U1<-do.call(cbind, UList) #la matrice del disegno sara' cbind(X, U1)
        #if (pow[1] != 1) U1 <- U1^pow[1]
        obj1 <- try(mylmWO(cbind(X, U1), y, w, offs), silent = TRUE)
        #if (class(obj1)[1] == "try-error") obj1 <- try(lm.wfit(cbind(X, U1), y, w, offs), silent = TRUE)
        L1 <- if (class(obj1)[1] == "try-error") L0 + 10 else obj1$L0
        L1
    }
  #=========
    search.min<-function(h, psi, psi.old, X, y, w, offs) {
      psi.ok<- psi*h + psi.old*(1-h)
      PSI <- matrix(psi.ok, n, ncol = length(psi.ok), byrow=TRUE)
      U1 <- (Z - PSI) * (Z > PSI)
      
      for(i in 1:length(RList)){#trasforma le U
        UList[[i]]<- cbind(Zseg[,i], U1[, id.psi.group==i])%*%invA.RList[[i]] #
        #nomiUList[[i]]<- rep(i, ncol(UList[[i]]) )
      }
      U1<-do.call(cbind, UList) #la matrice del disegno sara' cbind(X, U1)
      #if (pow[1] != 1) U1 <- U1^pow[1]
      obj1 <- try(mylm(cbind(X, U1), y), silent = TRUE)
      #if (class(obj1)[1] == "try-error") obj1 <- try(lm.wfit(cbind(X, U1), y, w, offs), silent = TRUE)
      L1 <- if (class(obj1)[1] == "try-error") L0 + 10 else obj1$L0
      L1
    }
    
    # est.k <- function(x1, y1, L0) {
    #     ax <- log(x1)
    #     .x <- cbind(1, ax, ax^2)
    #     b <- drop(solve(crossprod(.x), crossprod(.x, y1)))
    #     const <- b[1] - L0
    #     DD <- sqrt(b[2]^2 - 4 * const * b[3])
    #     kk <- exp((-b[2] + DD)/(2 * b[3]))
    #     return(round(kk))
    # }
    # dpmax <- function(x, y, pow = 1) {
    #     if (pow == 1) 
    #         -(x > y)
    #     else -pow * ((x - y) * (x > y))^(pow - 1)
    # }
    mylmWO <- function(x, y, w, offs = 0) {
      sw <- sqrt(w)  
      x1 <- x * sw
      y <- y - offs
      y1 <- y * sw
      b <- drop(solve(crossprod(x1), crossprod(x1, y1)))
      fit <- drop(x%*%b)
      r <- y - fit
      o <- list(coefficients = b, fitted.values = fit, residuals = r, L0=sum(w*r^2),
            df.residual = length(y) - length(b))
      o
    }
    mylm <- function(x, y, w, offs) {
      b <- drop(solve(crossprod(x), crossprod(x, y)))
      fit <- drop(x%*%b)
      r <- y - fit
      o <- list(coefficients = b, fitted.values = fit, residuals = r, L0=sum(r^2),
                df.residual = length(y) - length(b))
      o
    }
    id.w.offs <- var(offs)<=0 && var(w)<=0
    if(id.w.offs){
      fitter<-function(x, y, w, offs) .lm.fit(x=x, y=y) #list(coefficients=drop(solve(crossprod(x), crossprod(x, y))))
      mylmOK <- mylm
      search.minOK <- search.min
    } else {
      fitter<-function(x, y, w, offs) .lm.fit(x=sqrt(w)*x, y=sqrt(w)*(y-offs))
      mylmOK <- mylmWO
      search.minOK <- search.minWO
    }
    
    
    # isZero<-function (x, neps = 1, eps = .Machine$double.eps, ...) {
    #   if (is.character(eps)) {
    #     eps <- match.arg(eps, choices = c("double.eps", "single.eps"))
    #     if (eps == "double.eps") {
    #       eps <- .Machine$double.eps
    #     }
    #     else if (eps == "single.eps") {
    #       eps <- sqrt(.Machine$double.eps)
    #     }
    #   }
    #   (abs(x) < neps * eps)
    # }
    isZero <- function(v) sapply(v, function(.x) identical(.x,0))
    
    
    # mylmADD <- function(invXtX, X, v, Xty, y) {
    #     vtv <- sum(v^2)
    #     Xtv <- crossprod(X, v)
    #     m <- invXtX %*% Xtv
    #     d <- drop(1/(vtv - t(Xtv) %*% m))
    #     r <- -d * m
    #     invF <- invXtX + d * tcrossprod(m)
    #     newINV <- rbind(cbind(invF, r), c(t(r), d))
    #     b <- crossprod(newINV, c(Xty, sum(v * y)))
    #     fit <- tcrossprod(cbind(X, v), t(b))
    #     r <- y - fit
    #     o <- list(coefficients = b, fitted.values = fit, residuals = r)
    #     o
    # }
    in.psi <- function(LIM, PSI, ret.id = TRUE) {
        a <- PSI[1, ] <= LIM[1, ]
        b <- PSI[1, ] >= LIM[2, ]
        is.ok <- !a & !b
        if (ret.id) 
            return(is.ok)
        isOK <- all(is.ok) && all(!is.na(is.ok))
        isOK
    }
    far.psi <- function(Z, PSI, id.psi.group, ret.id = TRUE, fc = 0.93) {
        nSeg <- length(unique(id.psi.group))
        npsij <- tapply(id.psi.group, id.psi.group, length)
        nj <- sapply(unique(id.psi.group), function(.x) {
            tabulate(rowSums((Z > PSI)[, id.psi.group == .x, 
                drop = FALSE]) + 1)
        }, simplify = FALSE)
        ff <- id.far.ok <- vector("list", length = nSeg)
        for (i in 1:nSeg) {
            if (length(nj[[i]]) != npsij[i] + 1) 
                nj[[i]] <- tabulate(rowSums((Z >= PSI)[, id.psi.group == 
                  i, drop = FALSE]) + 1)
            id.ok <- (nj[[i]] >= 2)
            id.far.ok[[i]] <- id.ok[-length(id.ok)] & id.ok[-1]
            ff[[i]] <- ifelse(diff(nj[[i]]) > 0, 1/fc, fc)
        }
        id.far.ok <- unlist(id.far.ok)
        ff <- unlist(ff)
        if (!ret.id) {
            return(all(id.far.ok))
        }
        else {
            attr(id.far.ok, "factor") <- ff
            return(id.far.ok)
        }
    }
    adj.psi <- function(psii, LIM) {
        pmin(pmax(LIM[1, ], psii), LIM[2, ])
    }
    #nuovo per i vincoli

    RList <- opz$RList
    nomiUList<-UList<- vector("list",length(RList))
    invAList <- lapply(RList, function(.x)rbind(c(1,rep(0,nrow(.x)-1)),diff(diag(nrow(.x)))))
    invA.RList<-lapply(1:length(RList), function(i) invAList[[i]]%*% RList[[i]])
    nomiUList<- lapply(1:length(RList), function(i)rep(i, ncol(RList[[i]])))

    n <- length(y)
    min.step <- opz$min.step
    rangeZ <- apply(Z, 2, range)
    alpha <- opz$alpha #ha gia' 2 componenti! 
    #limZ <- apply(Z, 2, quantile, names = FALSE, probs = alpha) #c(alpha, 1 - alpha))
    limZ <- if(is.null(opz$limZ)) apply(Z, 2, quantile, names=FALSE, probs=c(alpha[1],alpha[2])) else opz$limZ
    #browser()
    #for(.i in opz$nomiSeg) { ##poni min(z)=0, cosi solve() in step.lm.fit non ha problemi.
    #  if(.i %in% colnames(XREG)) XREG[,.i] <- XREG[,.i] - min(XREG[,.i])
    #}
    
    psi <- PSI[1, ]
    id.psi.group <- opz$id.psi.group
    conv.psi <- opz$conv.psi
    hh <- opz$h
    digits <- opz$digits
    pow <- opz$pow
    nomiOK <- opz$nomiOK
    toll <- opz$toll
    gap <- opz$gap
    fix.npsi <- opz$stop.if.error
    dev.new <- opz$dev0
    visual <- opz$visual
    it.max <- old.it.max <- opz$it.max
    fc <- opz$fc
    names(psi) <- id.psi.group
    it <- 0
    epsilon <- 10
    k.values <- dev.values <- NULL
    psi.values <- list()
    #psi.values[[length(psi.values) + 1]] <- NA
    sel.col.XREG <- unique(sapply(colnames(XREG), function(x) match(x, 
        colnames(XREG))))
    if (is.numeric(sel.col.XREG)) 
        XREG <- XREG[, sel.col.XREG, drop = FALSE]
    invXtX <- opz$invXtX
    Xty <- opz$Xty
    if (!in.psi(limZ, PSI, FALSE)) 
        stop("starting psi out of the range.. see 'alpha' in seg.control.", 
            call. = FALSE)
    if (!far.psi(Z, PSI, id.psi.group, FALSE)) 
        stop("psi values too close each other. Please change (decreases number of) starting values", 
            call. = FALSE)
    n.psi1 <- ncol(Z)
    
    Zseg <- XREG[,opz$nomiSeg,drop=FALSE] #
    minZ<- apply(Zseg, 2, min)
    Zseg0<- Zseg
    Zseg <- sweep(Zseg, 2, minZ)  
    XREG <- XREG[, -match(opz$nomiSeg, colnames(XREG)),drop=FALSE]
    
    #browser()
    
    U <- ((Z - PSI) * (Z > PSI))
    #if (pow[1] != 1) U <- U^pow[1]
    
    for(i in 1:length(RList)){#trasforma le U
      UList[[i]]<- cbind(Zseg[,i], U[, id.psi.group==i])%*%invA.RList[[i]] #
      #nomiUList[[i]]<- rep(i, ncol(UList[[i]]) )
    }
    U<-do.call(cbind, UList) #la matrice del disegno sara' cbind(X, U)
    
    if(it.max==0){
      colnames(U) <- paste("U", 1:ncol(U), sep = "")
      V <- -(Z > PSI)
      colnames(V) <- paste("V", 1:ncol(V), sep = "")
      obj <- lm.wfit(x = cbind(XREG, U), y = y, w = w, offset = offs)
      L1 <- sum(obj$residuals^2 * w)
      obj$coefficients <- c(obj$coefficients, rep(0, ncol(V)))
      #names(obj$coefficients) <- names.coef
      obj$epsilon <- epsilon
      obj$it <- it
      obj <- list(obj = obj, it = it, psi = psi, psi.values = psi.values, X=XREG, idU=ncol(XREG)+1:(ncol(U)),
                  U = U, V = V, rangeZ = rangeZ, epsilon = epsilon, nomiOK = nomiOK, 
                  SumSquares.no.gap = L1, id.psi.group = id.psi.group, 
                  id.warn = TRUE, constr=list(RList=RList, invAList=invAList, invA.RList=invA.RList, nomiUList =nomiUList))
      return(obj)
    }
    
    obj0 <- try(mylmOK(cbind(XREG, U), y, w, offs), silent = TRUE)
    #if (class(obj0)[1] == "try-error") obj0 <- lm.wfit(cbind(XREG, U), y, w, offs)
    L0 <- obj0$L0 #sum(obj0$residuals^2 * w)
    
    
    
    n.intDev0 <- nchar(strsplit(as.character(L0), "\\.")[[1]][1])
    
    dev.values[length(dev.values) + 1] <- L0
    psi.values[[length(psi.values) + 1]] <- psi
    #browser()
    if (visual) {
        cat(paste("iter = ", sprintf("%2.0f", 0), "  dev = ", 
            sprintf(paste("%", n.intDev0 + 6, ".5f", sep = ""), 
                L0), "  k = ", sprintf("%2.0f", NA), "  n.psi = ", 
            formatC(length(unlist(psi)), digits = 0, format = "f"), 
            "  ini.psi = ", paste(formatC(unlist(psi), digits = 3, 
                format = "f"), collapse = "  "), sep = ""), "\n")
    }
    id.warn <- FALSE
    id.psi.changed <- rep(FALSE, it.max)
    #============================================== inizio ciclo
    #browser()
    #Zseg (a differenza di Z) ha una colonna per ogni variabile segmented, indipendentemente dal n.psi
    tolOp<-if(is.null(opz$tol.opt)) seq(.001, .Machine$double.eps^0.25, l=it.max) else rep(opz$tol.opt, it.max)
    idU <- ncol(XREG)+(1:ncol(U))
    idZ <- 1:length(psi) + max(idU)
    while (abs(epsilon) > toll) {
        it <- it + 1
        n.psi0 <- n.psi1
        n.psi1 <- ncol(Z)
        if (n.psi1 != n.psi0) {
            U <- ((Z - PSI) * (Z > PSI))
            #if (pow[1] != 1) U <- U^pow[1]
            obj0 <- try(mylm(cbind(XREG, U), y, w, offs), silent = TRUE)
            if (class(obj0)[1] == "try-error") 
                obj0 <- lm.wfit(cbind(XREG, U), y, w, offs)
            L0 <- sum(obj0$residuals^2 * w)
        } else {
          #V <- dpmax(Z, PSI, pow = pow[2])
          V <- (Z>PSI)
          U <- (Z - PSI) * V
          V <- -V
        }
        
        for(i in 1:length(RList)){#trasforma le U
          UList[[i]]<- cbind(Zseg[,i], U[, id.psi.group==i])%*%invA.RList[[i]] #
          nomiUList[[i]]<- rep(i, ncol(UList[[i]]) )
        }
        U<-do.call(cbind, UList)

        X <- cbind(XREG, U, V)
        #rownames(X) <- NULL
        #colnames(X)[(ncol(XREG) + 1):ncol(U)] <- paste("U", 
         #   1:ncol(U), sep = "") #, paste("V", 1:ncol(V), sep = ""))
        obj <- fitter(X, y, w, offs) #lm.wfit(x = X, y = y, w = w, offset = offs)
        beta.c <- obj$coefficients[idU]
        coefUList <- lapply(1:length(RList), function(i) (invA.RList[[i]]%*%beta.c[unlist(nomiUList)==i])[-1])
        beta.c <- unlist(coefUList)

        gamma.c <- obj$coefficients[idZ] #[colnames(Z)]
        if (any(isZero(c(beta.c, gamma.c)))) {
            if (fix.npsi) {
                if (return.all.sol) 
                  return(list(dev.values, psi.values))
                else stop("breakpoint estimate too close or at the boundary causing NA estimates.. too many breakpoints being estimated?", 
                  call. = FALSE)
            } else {
                id.coef.ok <- !isZero(gamma.c)
                psi <- psi[id.coef.ok]
                if (length(psi) <= 0) {
                  warning(paste("All breakpoints have been removed after", 
                    it, "iterations.. returning 0"), call. = FALSE)
                  return(0)
                }
                gamma.c <- gamma.c[id.coef.ok]
                beta.c <- beta.c[id.coef.ok]
                Z <- Z[, id.coef.ok, drop = FALSE]
                rangeZ <- rangeZ[, id.coef.ok, drop = FALSE]
                limZ <- limZ[, id.coef.ok, drop = FALSE]
                nomiOK <- nomiOK[id.coef.ok]
                id.psi.group <- id.psi.group[id.coef.ok]
                names(psi) <- id.psi.group
            }
        }
        psi.old <- psi
        psi <- psi.old + hh*gamma.c/beta.c
        #aggiusta la stima di psi..
        psi<- adj.psi(psi, limZ)
        psi<-unlist(tapply(psi, opz$id.psi.group, sort), use.names =FALSE)
        #browser()
        
        a<-optimize(search.min, c(0,1), psi=psi, psi.old=psi.old, X=XREG, y=y, w=w, offs=offs, tol=tolOp[it])
        k.values[length(k.values) + 1] <- use.k <- a$minimum
        L1<- a$objective
        #L1.k[length(L1.k) + 1] <- L1<- a$objective
        psi <- psi*use.k + psi.old* (1-use.k)
        psi<- adj.psi(psi, limZ)
        if (!is.null(digits)) psi <- round(psi, digits)
        PSI <- matrix(psi, n, ncol = length(psi), byrow = TRUE)
        U1 <- (Z - PSI) * (Z > PSI)

        #if (pow[1] != 1) U1 <- U1^pow[1]
        #obj1 <- try(mylm(cbind(XREG, U1), y, w, offs), silent = TRUE)
        #if (class(obj1)[1] == "try-error") obj1 <- try(lm.wfit(cbind(XREG, U1), y, w, offs), silent = TRUE)

        if (visual) {
            flush.console()
            cat(paste("iter = ", sprintf("%2.0f", it), 
                "  dev = ", sprintf(paste("%", n.intDev0 + 6, ".5f", sep = ""), L1), 
                "  k = ", sprintf("%2.3f", use.k), "  n.psi = ", formatC(length(unlist(psi)), digits = 0, format = "f"), 
                "  est.psi = ", paste(formatC(unlist(psi), digits = 3, format = "f"), collapse = "  "), sep = ""), "\n")
        }
        epsilon <-  (L0 - L1)/(abs(L0) + 0.1)
        L0 <- L1
        U <- U1
        k.values[length(k.values) + 1] <- use.k
        psi.values[[length(psi.values) + 1]] <- psi
        dev.values[length(dev.values) + 1] <- L0
        id.psi.far <- far.psi(Z, PSI, id.psi.group, TRUE, fc = opz$fc)
        id.psi.in <- in.psi(limZ, PSI, TRUE)
        id.psi.ok <- id.psi.in & id.psi.far
        if (!all(id.psi.ok)) {
            if (fix.npsi) {
                psi <- psi * ifelse(id.psi.far, 1, attr(id.psi.far, 
                  "factor"))
                PSI <- matrix(rep(psi, rep(nrow(Z), length(psi))), 
                  ncol = length(psi))
                id.psi.changed[it] <- TRUE
            } else {
                Z <- Z[, id.psi.ok, drop = FALSE]
                PSI <- PSI[, id.psi.ok, drop = FALSE]
                rangeZ <- rangeZ[, id.psi.ok, drop = FALSE]
                limZ <- limZ[, id.psi.ok, drop = FALSE]
                nomiOK <- nomiOK[id.psi.ok]
                id.psi.group <- id.psi.group[id.psi.ok]
                psi.old <- psi.old[id.psi.ok]
                psi <- psi[id.psi.ok]
                names(psi) <- id.psi.group
                if (ncol(PSI) <= 0) {
                  warning(paste("All breakpoints have been removed after", 
                    it, "iterations.. returning 0"), call. = FALSE)
                  return(0)
                }
            }
        }
        if (it >= it.max) {
            id.warn <- TRUE
            break
        }
    } #end while..
    ##############################################################################
    if (id.psi.changed[length(id.psi.changed)]) 
        warning(paste("Some psi (", (1:length(psi))[!id.psi.far], 
            ") changed after the last iter.", sep = ""), call. = FALSE)
    if (id.warn) 
        warning(paste("max number of iterations (", it, ") attained", 
            sep = ""), call. = FALSE)
    attr(psi.values, "dev") <- dev.values
    attr(psi.values, "k") <- k.values
    psi <- unlist(tapply(psi, id.psi.group, sort))
    names(psi) <- id.psi.group
    names.coef <- names(obj$coefficients)
    #PSI.old <- PSI
    PSI <- matrix(psi, n, ncol = length(psi), byrow = TRUE)
    #if (sd(PSI - PSI.old) > 0 || id.psi.changed[length(id.psi.changed)]) {
    #browser()
    V <- -(Z > PSI)
    colnames(V) <- paste("V", 1:ncol(V), sep = "")
    
    U <- (Z - PSI) * (Z > PSI)
    for(i in 1:length(RList)){#trasforma le U
      UList[[i]]<- cbind(Zseg0[,i], U[, id.psi.group==i])%*%invA.RList[[i]] 
      nomiUList[[i]]<- rep(i, ncol(UList[[i]]) )
    }
    U<-do.call(cbind, UList) #X <- cbind(XREG, U, V)

    colnames(U) <- paste("U", 1:ncol(U), sep = "")
    
    
    #obj <- mylmOK(x = cbind(XREG, U), y = y, w = w, offs = offs)
    #L1 <- obj$L0
    
    #browser()
    
    obj <- fitter(cbind(XREG, U), y, w, offs) #lm.wfit()
    #obj <- lm.wfit(cbind(XREG, U), y, w, offs)
    L1 <- sum(obj$residuals^2 * w)
    
    #browser()
    
    #idInt<-match("(Intercept)", names(obj$coefficients),0)
    #obj$coefficients[idInt] <-  obj$coefficients[idInt]-sum(obj$coefficients[opz$nomiSeg]*minZ)
    
    obj$coefficients <- c(obj$coefficients, rep(0, ncol(V)))
    obj$df.residual <- length(y) - length(obj$coefficients)
    obj$fitted.values <- y - obj$residuals
    #names(obj$coefficients) <- names.coef
    obj$epsilon <- epsilon
    obj$it <- it
    obj <- list(obj = obj, it = it, psi = psi, psi.values = psi.values, X=XREG, idU=ncol(XREG)+1:(ncol(U)),
        U = U, V = V, rangeZ = rangeZ, epsilon = epsilon, nomiOK = nomiOK, 
        SumSquares.no.gap = L1, id.psi.group = id.psi.group, id.warn = id.warn, 
        constr=list(RList=RList, invAList=invAList, invA.RList=invA.RList, nomiUList =nomiUList))
    #SlopeList <- lapply(1:length(RList), function(i) RList[[i]]%*%beta.c[unlist(nomiUList)==i])
    return(obj)
}