Description Usage Arguments Details Value References See Also Examples
Predicts Heligman-Pollard model from Heligman-Pollard's parameters.
1 |
life |
A life table created with life.tab or a dataframe with a vector of ages in the first column. |
HPout |
A model object created with HP.mod with the Heligman-Pollard estimated params. |
M |
Defines the statistic to predict. Median by default (med), Low CI (low) or High CI (high) |
age |
A vector containing the ages at which each age interval begins. See Details |
rm |
The number of age classes that want to be removed from optimization. |
Mx is returned only if number of ages required for prediction is equal to the number of ages in the life table.
A dataframe with seven columns:
age |
Age at the beginning of the interval. |
Mx |
Number of observed deaths at age x. |
qx.tot |
Total probability of death between ages x and x + n. |
qx.nat |
Natural probability of death between ages x and x + n. |
qx.young |
Young probability of death between ages x and x + n. |
qx.risk |
Probability of death due to an externl risk between ages x and x + n. |
qx.adult |
Adult or senescent probability of death between ages x and x + n. |
Heligman, L. and Pollard, J.H. (1980). The Age Pattern of Mortality. Journal of the Institute of Actuaries 107:49<e2><80><93>80.
Sharrow, D.J., Clark, S.J., Collinson, M.A., Kahn, K. and Tollman, S.M. (2013). The Age Pattern of Increases in Mortality Affected by HIV: Bayesian Fit of the Heligman-Pollard Model to Data from the Agincourt HDSS Field Site in Rural Northeast South Africa. Demogr. Res. 29, 1039<e2><80><93>1096.
HP.mod
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | lifeN <- life.tab(cetaceans)
modSi <- Si.mod(data = cetaceans, rm = 2,
par = c(0.3159462, 0.1860541, -1.2802880, 1.1733226, 0.0170314))
dataSi <- Si.pred(data = cetaceans, Sout = modSi, rm = 2)
priors <- data.frame(priors.lo = c(0,0.5,0,0,0,0,6,0,1),
priors.hi = c(0.1,1,1,0.15,0.15,50,10,0.01,1.5))
q0 <- HP.priors(pri.lo = priors$priors.lo,
pri.hi = priors$priors.hi,
theta.dim = 9)
modHP <- HP.mod(prior = q0, lifeTab = lifeN, rm = 2, K = 10, d = 10, B = 10, CI = 90)
HP.pred(life = lifeN, HPout = modHP, age = seq(0,29,1), rm = 2)
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