MOREMATA: Stata module (Mata) to provide various functions

This package includes various Mata functions. kern(): various kernel functions; kint(): kernel integral functions; kdel0(): canonical bandwidth of kernel; quantile(): quantile function; median(): median; iqrange(): inter-quartile range; ecdf(): cumulative distribution function; relrank(): grade transformation; ranks(): ranks/cumulative frequencies; freq(): compute frequency counts; histogram(): produce histogram data; mgof(): multinomial goodness-of-fit tests; collapse(): summary statistics by subgroups; _collapse(): summary statistics by subgroups; gini(): Gini coefficient; sample(): draw random sample; srswr(): SRS with replacement; srswor(): SRS without replacement; upswr(): UPS with replacement; upswor(): UPS without replacement; bs(): bootstrap estimation; bs2(): bootstrap estimation; bs_report(): report bootstrap results; jk(): jackknife estimation; jk_report(): report jackknife results; subset(): obtain subsets, one at a time; composition(): obtain compositions, one by one; ncompositions(): determine number of compositions; partition(): obtain partitions, one at a time; npartitionss(): determine number of partitions; rsubset(): draw random subset; rcomposition(): draw random composition; colvar(): variance, by column; meancolvar(): mean and variance, by column; variance0(): population variance; meanvariance0(): mean and population variance; mse(): mean squared error; colmse(): mean squared error, by column; sse(): sum of squared errors; colsse(): sum of squared errors, by column; benford(): Benford distribution; cauchy(): cumulative Cauchy-Lorentz dist.; cauchyden(): Cauchy-Lorentz density; cauchytail(): reverse cumulative Cauchy-Lorentz; invcauchy(): inverse cumulative Cauchy-Lorentz; rbinomial(): generate binomial random numbers; cebinomial(): cond. expect. of binomial r.v.; root(): Brent's univariate zero finder; nrroot(): Newton-Raphson zero finder; finvert(): univariate function inverter; integrate_sr(): univariate function integration (Simpson's rule); integrate_38(): univariate function integration (Simpson's 3/8 rule); ipolate(): linear interpolation; polint(): polynomial inter-/extrapolation; plot(): Draw twoway plot; _plot(): Draw twoway plot; panels(): identify nested panel structure; _panels(): identify panel sizes; npanels(): identify number of panels; nunique(): count number of distinct values; nuniqrows(): count number of unique rows; isconstant(): whether matrix is constant; nobs(): number of observations; colrunsum(): running sum of each column; linbin(): linear binning; fastlinbin(): fast linear binning; exactbin(): exact binning; makegrid(): equally spaced grid points; cut(): categorize data vector; posof(): find element in vector; which(): positions of nonzero elements; locate(): search an ordered vector; hunt(): consecutive search; cond(): matrix conditional operator; expand(): duplicate single rows/columns; _expand(): duplicate rows/columns in place; repeat(): duplicate contents as a whole; _repeat(): duplicate contents in place; unorder2(): stable version of unorder(); jumble2(): stable version of jumble(); _jumble2(): stable version of _jumble(); pieces(): break string into pieces; npieces(): count number of pieces; _npieces(): count number of pieces; invtokens(): reverse of tokens(); realofstr(): convert string into real; strexpand(): expand string argument; matlist(): display a (real) matrix; insheet(): read spreadsheet file; infile(): read free-format file; outsheet(): write spreadsheet file; callf(): pass optional args to function; callf_setup(): setup for mm_callf().

Meteorological data, stem radius measurements (SR) and derivates of SR of the three Swiss forest sites Visp, Davos and Lägeren

. Separating continuously measured stem radius (SR) fluctuations into growth-induced irreversible stem expansion (GRO) and tree water deficit-induced reversible stem shrinkage (TWD) requires a concept to decide on potential growth processes during periods of shrinking and expanding SR below a precedent maximum. Here we investigated two physiological concepts: the linear growth (LG) concept assuming linear growth vs. the zero growth (ZG) concept assuming no growth during periods of shrunken stems. . We evaluated the physiological mechanisms underlying these two concepts and assessed the respective plausibility with SR data obtained from 15 deciduous and evergreen trees. . The LG concept showed steady growth rates, whereas the ZG concept showed strongly varying growth rates over time, more in accordance with mechanistic expectations. Further, growth increased for maximally 120 min after periods of shrunken stems, indicating limited growth activity during that period. However, the fraction of this extra growth was found to be small. Furthermore, TWD of the ZG concept was better explained by a hydraulic plant model than TWD of the LG concept. . We conclude that periods of shrunken stems allow for very little growth in the four tree species investigated. However, further studies should focus on obtaining independent growth data to ultimately validate these findings.

Stable isotopes and XRF data over the Paleocene-Eocene Thermal Maximum from IODP Sites U1403 and U1409

During the Paleocene-Eocene Thermal Maximum (PETM) about 56 million years ago, thousands of petagrams of carbon were released into the atmosphere and ocean in just a few thousand years, followed by a gradual sequestration over approximately 200,000 years. If silicate weathering is one of the key negative feedbacks that removed this carbon, a period of seawater calcium carbonate saturation greater than pre-event levels is expected during the event's recovery phase. In marine sediments, this should be recorded as a temporary deepening of the depth below which no calcite is preserved - the calcite compensation depth (CCD). Previous and new sedimentary records from sites that were above the pre-PETM calcite compensation depth show enhanced carbonate accumulation following the PETM. A new record from an abyssal site in the North Atlantic that lay below the pre-PETM calcite compensation depth shows a period of carbonate preservation beginning about 70,000 years after the onset of the PETM, providing the first direct evidence for an over-deepening of the calcite compensation depth. This record confirms an overshoot in ocean carbonate saturation during the PETM recovery. Simulations with two earth system models support scenarios for the PETM that involve both a large initial carbon release followed by prolonged low-level emissions, consistent with the timing of CCD deepening in our record. Our findings indicate that sequestration of these carbon emissions was most likely the result of both globally enhanced calcite burial above the calcite compensation depth and, at least in the North Atlantic, by a temporary over-deepening of the calcite compensation depth.

Truck traffic volume and weight data for 1971 and their evaluation. Final report.

Mode of access: Internet.

Laboratory data and descriptions of soils of the Benchmark Soils Project /

"TRBSP-05-11/79(1 M)"--v.2

Maine occupational staffing for selected nonmanufacturing industries : mining, construction, finance, insurance, and real estate services, except hospitals and education : data for second quarter 1990 /

"Issued July 1992."

Maine occupational staffing for selected nonmanufacturing industries : construction, finance, insurance, and real estate services, except hospitals and education : data for second quarter 1993 /

"Issued December 1994."

Antiretroviral Treatment as Prevention in African HIV-1 Serodiscordant Couples: Understanding the Challenges and Opportunities

Thesis (Ph.D.)--University of Washington, 2016-06

White blood cell count predicts reduction in coronary heart disease mortality with pravastatin

Background-Elevated serum inflammatory marker levels are associated with a greater long-term risk of cardiovascular events. Because 3-hydroxy-3-methylglutaryl coenzyme-A reductase inhibitors (statins) may have an antiinflammatory action, it has been suggested that patients with elevated inflammatory marker levels may have a greater reduction in cardiovascular risk with statin treatment. Methods and Results-We evaluated the association between the white blood cell count (WBC) and coronary heart disease mortality during a mean follow-up of 6.0 years in the Long-Term Intervention With Pravastatin in Ischemic Disease (LIPID) Study, a clinical trial comparing pravastatin (40 mg/d) with a placebo in 9014 stable patients with previous myocardial infarction or unstable angina. An increase in baseline WBC was associated with greater coronary heart disease mortality in patients randomized to placebo (hazard ratio for 1 X 10(9)/L increase in WBC, 1.18; 95% CI, 1.12 to 1.25; P<0.001) but not pravastatin (hazard ratio, 1.02; 95% CI, 0.96 to 1.09; P=0.56; P for interaction=0.004). The numbers of coronary heart disease deaths prevented per 1000 patients treated with pravastatin were 0, 9, 30, and 38 for baseline WBC quartiles of <5.9, 6.0 to 6.9, 7.0 to 8.1, and >8.2X10(9)/L, respectively. WBC was a stronger predictor of this treatment benefit than the ratio of total to high-density lipoprotein cholesterol and a global measure of cardiac risk. There was also a greater reduction (P=0.052) in the combined incidence of cardiovascular mortality, nonfatal myocardial infarction, and stroke with pravastatin as baseline WBC increased ( by quartile: 3, 41, 61, and 60 events prevented per 1000 patients treated, respectively). Conclusions-These data support the hypothesis that individuals with evidence of inflammation may obtain a greater benefit from statin therapy.

Zero-non-zero patterned vector error correction modeling for I(2) cointegrated time series with applications in testing PPP and stock market relationships

Vector error-correction models (VECMs) have become increasingly important in their application to financial markets. Standard full-order VECM models assume non-zero entries in all their coefficient matrices. However, applications of VECM models to financial market data have revealed that zero entries are often a necessary part of efficient modelling. In such cases, the use of full-order VECM models may lead to incorrect inferences. Specifically, if indirect causality or Granger non-causality exists among the variables, the use of over-parameterised full-order VECM models may weaken the power of statistical inference. In this paper, it is argued that the zero–non-zero (ZNZ) patterned VECM is a more straightforward and effective means of testing for both indirect causality and Granger non-causality. For a ZNZ patterned VECM framework for time series of integrated order two, we provide a new algorithm to select cointegrating and loading vectors that can contain zero entries. Two case studies are used to demonstrate the usefulness of the algorithm in tests of purchasing power parity and a three-variable system involving the stock market.

Reference values for whole body and cerebral multi-frequency bio-impedance data in neonates less than 12 h postpartum

Multiple frequency bio-electrical impedance analysis (MFBIA) may be useful for monitoring fluid balance in newborn infants or to provide early prediction of the outcome following perinatal asphyxia. A reference range of data is needed for identification of babies with abnormal impedance values. This was a cross-sectional observational study in 84 term and near-term healthy neonates less than 12 h postpartum. Whole body and cerebral MFBIA measurements were performed at the bedside in the post-natal ward. Gestational age, post-natal age, gender, birthweight, head circumference and foot length measures were recorded. Reference values for impedance at the characteristic frequency (Z(C)) and resistance at zero frequency (R-0) are reported for whole body and cerebral impedance. Significant correlations (p < 0.05) were observed between whole body impedance and birthweight, footlength and head circumference. Females had a significantly higher whole body R0 than males. Cerebral impedance did not correlate significantly with any of the demographic measures and therewere no gender differences observed for cerebral impedance. The reference range for whole body multi-frequency bio-impedance values in term and near-term infants within the first 12 h postpartum can be calculated from the footlength (FL) using the following equations: Z(C) = (942.9 - 4.818* FL) +/- 124.6 Omega; R-0 = (1042 - 4.520(*)FL) +/- 135.5 Omega. For cerebral impedance the reference range is 29.5-48.7 Omega for Z(C) and 33.7-58.0 Omega for R-0.

Statnote 16: fitting a regression line to data

Fitting a linear regression to data provides much more information about the relationship between two variables than a simple correlation test. A goodness of fit test of the line should always be carried out. Hence, ‘r squared’ estimates the strength of the relationship between Y and X, ANOVA whether a statistically significant line is present, and the ‘t’ test whether the slope of the line is significantly different from zero. In addition, it is important to check whether the data fit the assumptions for regression analysis and, if not, whether a transformation of the Y and/or X variables is necessary.