visited isaiah's school. sunday dinner at ruth's house with custom
armoire, we ate beans and okra and eggplant and polenta and watermelon
and
do you like pineapple?
i love pineapple
great, today is your day
rest atop one of seven hills, a potential energy hoard. butterfly benjamin button'd become . . . a caterpillar? why're we wired to record the days?
find suggestion agreement, unclear on grammar syntactician. humble
captcha reminds despite our prosperity & wit, we've yet to replicate
ourselves
organize discussions of professional expertise to make friends, zero failures so far. christine (from arua) a few hours after our meal: am still satisfied
dream what mozart'd have done, electric bass & kit of drum. 'sadder huckabee in military kit and/or lula learned nought from the biden hubris family
yelled scram at a domino's pizza abroad then realized the futility of the moment. guh guh ghost in forty nine syllables, present tense death fascinates
pair an ear and spare a quid
for a séance or a kid
'fore four eyes flashed two lifes rid
coiled basket cobra hid
till i frisbee-tossed the lid
bede & me goodbyes bid
damndest thing i ever did
submitted a ltte
Official Statisticians Should Abandon Proprietary Software
The
cost-cutting drive spearheaded by Josh Gruenbaum ("Procurement chief
vows to continue supplier price squeeze", Report, July 22) would win
plaudits from nearly all segments of society if accompanied by a review
of open source technologies. Agencies like the U.S. Census Bureau and
the broader Federal Statistical System deserve neverending praise for
their global standard-setting commitment to publicly available,
respondent-level datasets (often termed microdata). Major research
initiatives like the Current Population Survey can be downloaded with
ease, on an annual basis, dating back to the JFK era. Unfortunately,
whether due to entrenched interests or perceived changeover costs,
government choice of analysis software has not yet made commensurate strides.
During the final quarter of the twentieth century, only closed-source tools like SAS (previously known as the "Statistical Analysis System") were capable of digesting what was then considered big data and, lacking alternatives, quantitative offices within the federal workforce grew reliant on this expensive, subscription-based syntax. But SAS and its proprietary peers continue to dominate government-funded research efforts even as top-tier universities enter their third decade training graduates in computing languages built for this side of the millenium - I first encountered the free & open-licensed R project at JHSPH in 2007 and have not looked back.
During the final quarter of the twentieth century, only closed-source tools like SAS (previously known as the "Statistical Analysis System") were capable of digesting what was then considered big data and, lacking alternatives, quantitative offices within the federal workforce grew reliant on this expensive, subscription-based syntax. But SAS and its proprietary peers continue to dominate government-funded research efforts even as top-tier universities enter their third decade training graduates in computing languages built for this side of the millenium - I first encountered the free & open-licensed R project at JHSPH in 2007 and have not looked back.
I would encourage anyone
skeptical of the maturity of the open source community to skim the
"Official Statistics CRAN Task View" page and find there detailed
explanations of advanced technologies freely available to all. To follow
Mr. Gruenbaum's principle, I challenge closed-source enterprises to
explain to a 15-year-old (or anyone else) why they deserve taxpayer
dollars where superior tools can be had for nothing. I commend my many
colleagues committed to reproducible research and transparent methods,
and I ask federal agencies to similarly aim toward this forward-looking
paradigm.
Anthony Damico
Washington D.C.
8/7