Function reference • DemoTools

Evaluate age structure Indicators to evaluate the degreee of age heaping
`check_heaping_bachi()`	calculate Bachi's index of age heaping
`check_heaping_coale_li()`	Coale-Li age heaping index
`check_heaping_jdanov()`	Calculate Jdanov's old-age heaping index
`check_heaping_kannisto()`	Kannisto's age heaping index
`check_heaping_myers()`	Calculate Myer's blended index of age heaping
`check_heaping_noumbissi()`	calculate Noumbissi's digit heaping index
`check_heaping_roughness()`	Evaluate roughness of data in 5-year age groups
`check_heaping_sawtooth()`	Detect if heaping is worse on terminal digits 0s than on 5s
`check_heaping_spoorenberg()`	Spoorenberg's total modified Whipple index
`check_heaping_whipple()`	Calculate Whipple's index of age heaping
Evaluate consistency of age structures Methods to assess the consistency of age structures
`ageRatioScore()`	Calculate the PAS age ratio score
`sexRatioScore()`	Calculate the PAS sex ratio score
`ageSexAccuracy()`	Calculate an age-sex accuracy index
`IRD()`	Index of relative difference.
`ID()`	Index of dissimilarity
`survRatioError()`	Census survival estimation
Evaluate patterns of heaping Methods to assess in which ages heaping happens
`check_heaping_sawtooth()`	Detect if heaping is worse on terminal digits 0s than on 5s
`check_heaping_roughness()`	Evaluate roughness of data in 5-year age groups
Graduation Functions to graduate demographic counts. Methods include Sprague, Beers ordinary, Beers modified, monotone spline, PCLM and uniform.
`graduate()`	Graduate grouped data
Smoothing Functions to smooth demographic counts. Methods include Carrier-Farrag, KKN, Arriaga, United Nations, Strong, spencer, Zigzag, Zelnik, MAV.
`smooth_age_5()`	Smooth populations in 5-year age groups using various methods
`agesmth1()`	Generic smoother over age or time
Lifetable Functions to construct a lifetable
`lt_abridged()`	Calculate an abridged-age lifetable.
`lt_single_mx()`	calculate a single age lifetable
`lt_single_qx()`	calculate a single age lifetable from qx
`lt_single2abridged()`	calculate an abridged life table that is consistent with a life table by single year of age
`lt_abridged2single()`	create a life table by single year of age by graduating an abridged life table
`lt_ambiguous()`	calculate an abridged or single age lifetable from abridged or single age data
`lt_smooth_ambiguous()`	Smooth and apply lt_ambiguous
Interpolation Functions to interpolate counts
`interp()`	Interpolate between two population age distributions.
`interp_coh()`	Cohort component intercensal interpolation
Extrapolation Functions to interpolate/extrapolate rates or counts
`interp_lc_lim()`	Lee-Carter method with limited data.
`lt_rule_m_extrapolate()`	Extrapolate old-age human mortality curve using mortality laws
`OPAG()`	Redistribute population over a specified age based on a stable standard fit to the data
Migration Functions for migration models or estimation
`mig_beta()`	Estimate intercensal migration by comparing census population, by age and sex, to the results of a RUP projection.
`mig_calculate_rc()`	Calculate Rogers-Castro migration age schedule
`mig_estimate_rc()`	Estimate Rogers-Castro migration age schedule
`mig_resid()` `mig_resid_stock()` `mig_resid_cohort()` `mig_resid_time()`	Estimate net migration using residual methods: stock change, time even flow and cohort even flow
`mig_un_fam()`	Net migration by age for an UN family
`mig_un_families`	Proportion of net migrants by age and sex for considered migration profiles
`mig_un_params`	Parameters for considered migration profiles
Miscelaneous data operations
`groupAges()`	Group single ages into equal age groups of arbitrary width
`rescaleAgeGroups()`	rescale counts in age groups to match counts in different age groups
Internal graduation
`graduate_beers()`	The ordinary modified Beers splitting methods
`graduate_beers_expand()`	Create the Beers ordinary or modified coefficient matrix
`graduate_beers_johnson()`	Adjust ages under 10 using a modification of Beers
`graduate_grabill()`	The basic Grabill age-splitting method
`graduate_grabill_expand()`	Create the Grabill coefficient matrix.
`graduate_mono()`	Graduate age groups using a monotonic spline.
`graduate_mono_closeout()`	blend the Sprague upper boundary age estimates into monotonic spline estimates
`graduate_pclm()`	wrapper for `ungroup::pclm` method of splitting binned counts
`graduate_sprague()`	The basic Sprague age-splitting method.
`graduate_sprague_expand()`	Create the Sprague coefficient matrix.
`graduate_uniform()`	Convert arbitrary age groupings into single years of age.
`splitOscillate()`	An oscillatory average of age splits.
Internal smoothing
`smooth_age_5()`	Smooth populations in 5-year age groups using various methods
`smooth_age_5_arriaga()`	E. Arriaga's method of population count smoothing
`smooth_age_5_cf()`	The Carrier-Farrag method of population count smoothing
`smooth_age_5_feeney()`	Feeney'S formula on 9 years to correct for heaping on multiples of 5.
`smooth_age_5_kkn()`	Karup-King-Newton method of population count smoothing
`smooth_age_5_mav()`	Smooth in 5-year age groups using a moving average
`smooth_age_5_strong()`	A strong method of population count smoothing
`smooth_age_5_un()`	The old United Nations method of population count smoothing
`smooth_age_5_zigzag()`	G. Feeney's method of smoothing counts in 5-year age groups.
`smooth_age_5_zigzag_inner()`	G. Feeney's method of removing the zigzag from counts in 5-year age groups.
`smooth_age_5_zigzag_min()`	Objective function to minimize Feeney's zigzag method residual
`smooth_age_5_zigzag_p()`	Smooth population counts using Feeney's zigzag method and smoothing parameters.
`agesmth1()`	Generic smoother over age or time
`loess_smth1()`	Wrapper to LOESS using demographic data.
`poly_smth1()`	Fit a polynomial to demographic data
`spencer()`	Smoothing of an age structure by single years using Spencer's formula.
`zelnik()`	Zelnik 11-term moving average to adjust for digit preference.
Auxiliary lifetable functions
`lt_a_closeout()`	Life expectancy in the open age group.
`lt_a_pas()`	PAS a(x) rule of thumb.
`lt_a_un()`	UN a(x) estimates from either M(x), q(x), or both
`lt_abridged()`	Calculate an abridged-age lifetable.
`lt_abridged2single()`	create a life table by single year of age by graduating an abridged life table
`lt_ambiguous()`	calculate an abridged or single age lifetable from abridged or single age data
`lt_id_L_T()`	Derive lifetable total person years left to live from exposure.
`lt_id_Ll_S()`	Calculate survivor ratios
`lt_id_d_l()`	Derive survivorship from lifetable deaths
`lt_id_d_q()`	Derive death probabilities from lifetable deaths
`lt_id_l_d()`	Derive lifetable deaths from survivorship.
`lt_id_l_q()`	Derive lifetable death probabilities from survivorship.
`lt_id_lda_L()`	Derive lifetable exposure from lx, ndx and nax.
`lt_id_ma_q()`	Calculate conditional death probabilities from nMx and nax
`lt_id_morq_a()`	wrapper to invoke PAS or UN ax methods given qx or mx
`lt_id_morq_a_greville()`	UN version of the Greville formula for a(x) from M(x)
`lt_id_q_l()`	Derive lifetable survivorship (lx) from death probabilities.
`lt_id_qa_m()`	Derive nMx from nqx and nax.
`lt_id_qm_a()`	Derive nax from nqx and nMx.
`lt_model_lq()`	Estimate Wilmoth Model Life Table
`lt_rule_1a0()`	calculate a0 in different ways
`lt_rule_1a0_ak()`	Andreev-Kingkade approximation for a0
`lt_rule_1a0_cd()`	Coale-Demeny a(0) as function of m(0), region, and sex.
`lt_rule_4a1_cd()`	Coale-Demeny 4a1 as function of M(0), region, and sex.
`lt_rule_4m0_D0()`	rule of thumb for splitting infants from deaths under 5
`lt_rule_4m0_m0()`	rule of thumb for estimating infant mortality rate from under 5 mortality
`lt_rule_ak_m0_a0()`	estimates a0 using the Andreev-Kingkade rule of thumb starting with an event exposure rate
`lt_rule_ak_q0_a0()`	estimates a0 using the Andreev-Kingkade rule of thumb starting with IMR
`lt_rule_m_extrapolate()`	Extrapolate old-age human mortality curve using mortality laws
`lt_single2abridged()`	calculate an abridged life table that is consistent with a life table by single year of age
`lt_single_mx()`	calculate a single age lifetable
`lt_single_qx()`	calculate a single age lifetable from qx
`lt_smooth_ambiguous()`	Smooth and apply lt_ambiguous
`single2abridged()`	Convert single age groups to five-year group abridged
Auxiliary checking functions
`is_abridged()`	Detect if a vector of lower age bounds is plausibly of abridged ages.
`is_age_coherent()`	check for coherence within Age and between Age and AgeInt
`is_age_redundant()`	check for redundant age specification
`is_age_sequential()`	is `Age` sorted sequentially?
`is_single()`	Logical checking of whether age classes appear single.
Datasets
`pop1m_ind`	Indian male population 1971
`pop1m_pasex`	Male population by 1 year age groups
`pop1m_rus2002`	Russian census 2002 male population by 1 year age groups
`pop1m_rus2010`	Russian census 2010 male population by 1 year age groups
`pop5_mat`	Matrix of population over 5 years
`pop5m_pasex`	Male population by 5 year age groups
`popA_earlier`	Abridged population from PAS AGEINT -- earlier
`popA_later`	Abridged population from PAS AGEINT -- later
`pop_f_mat_five`	Population matrix for females five year age groups between 1950 and 2050
`pop_f_mat_single`	Population matrix for females single ages between 1999 and 2019
`pop_m_mat_five`	Population matrix for males five year age groups between 1950 and 2050
`pop_m_mat_single`	Population matrix for males single ages between 1999 and 2019
Auxiliary population structure functions
`basepop_five()`	BPA and BPE methods for adjusting age groups under 10
`calcAgeN()`	Calculate which large age group single ages belong to.
`shift_census_ages_to_cohorts()`	shift census populations to match single year cohorts
`dec.date()`	Convert date to decimal year fraction.
`dth5_zigzag`	Deaths by 5 year age groups
`fitted_logquad_b`	LogQuad model for BOTH SEX fitted for all HMD life tables
`fitted_logquad_f`	LogQuad model for FEMALES fitted for all HMD life tables
`fitted_logquad_m`	LogQuad model for MALES fitted for all HMD life tables
Internal Internal functions
`OPAG_fit_stable_standard()`	creates stable standard based on optimizing the growth rate
`OPAG_nLx_warp_r()`	Warps a given stationary population into a stable population
`OPAG_r_min()`	calculates residual for optimizing growth rate r for OPAG family
`OPAG_simple()`	redistribute an open age group count over higher ages proportional to an arbitrary standard
`downloadSRB()`	Extract SRB estimates from WPP2019
`downloadnLx()`	Extract Lx estimates from WPP2019. Mainly an util function for other ones.
`ADM()`	Mean absolute difference in survival rates.
`age2ageN()`	repeat age lower bounds once for each single age
`age2int()`	Infer age class intervals from lower age bounds.
`AGEN()`	Trim two age vectors to matching N-year age groups.
`ageSexAccuracyDasGupta()`	Calculate Das Gupta's (1995) age sex accuracy index
`age_abridge_force()`	force a (count) vector to abridged ages
`avg_adj()`	calculate average of vector elements adjacent to and excluding the index element
`birthCohorts()`	Create the historical birth cohorts for a census.
`calcAgeAbr()`	Calculate which abridged age group single ages belong to.
`getModelLifeTable()`	Wrapper to provide a single location to reference all model life tables.
`groupAges()`	Group single ages into equal age groups of arbitrary width
`groupOAG()`	Group down to a new open age class.
`heapify()`	Induce heaping on terminal digits 0 and 5
`inferAgeIntAbr()`	Infer abridged age groups widths.
`int2age()`	Infer lower age bounds from age class intervals.
`int2ageN()`	repeat age lower bounds once for each single age
`interpolatePop()`	Interpolate between two population age distributions.
`ma()`	A simple centered moving average function.
`mav()`	Calculate the moving average (mav) over 3 or 5 years.
`maxA2abridged()`	Determine abridged ages up to a given maximum age group.
`names2age()`	detect ages from names of vector(s)
`ratx()`	Take consecutive ratios of a vector.
`rescale_vector()`	Rescale a vector proportionally to a new sum.
`RDM()`	Mean absolute difference in age-ratios of survival rates.
`rlog()`	Logging that does not cause jams.
`shift.vector()`	Shift a vector left or right.
`simplify.text()`	convert strings to concatenation of lower case alphabet
`surv10()`	Estimate survival curve from censuses spaced 10 years apart.
`surv5()`	Estimate survival curve from censuses spaced 5 years apart.
`survN()`	Estimate survival curve from censuses spaced N years apart.

Reference

Evaluate age structure

Evaluate consistency of age structures

Evaluate patterns of heaping

Graduation

Smoothing

Lifetable

Interpolation

Extrapolation

Migration

Miscelaneous data operations

Internal graduation

Internal smoothing

Auxiliary lifetable functions

Auxiliary checking functions

Datasets

Auxiliary population structure functions

Internal