Methods library of embedded R functions at Statistics Norway

Statistics Norway is modernising the production processes. An important element in this work is a library of functions for statistical computations. In principle, the functions in such a methods library can be programmed in several languages. A modernised production environment demand that these functions can be reused for different statistics products, and that they are embedded within a common IT system. The embedding should be done in such a way that the users of the methods do not need to know the underlying programming language. As a proof of concept, Statistics Norway soon has established a methods library offering a limited number of methods for macro-editing, imputation and confi dentiality. This is done within an area of municipal statistics with R as the only programming language. This paper presents the details and experiences from this work. The problem of fi tting real word applications to simple and strict standards is discussed and exemplifi ed by the development of solutions to regression imputation and table suppression. Keywords: Offi cial statistics, R; Common Statistical Production Architecture, Generic Statistical Information Model, Validation and Transformation Language, Imputation, Statistical disclosure control JEL Classifi cation: C18, C88publishedVersio

Automatic outlier handling and model selection in seasonal adjustment – A history analysis study involving three suggested outlier algorithms

The first part of this paper presents the most important results from a history analysis of 52 Norwegian economic time series (Langsrud, 2011). It is illustrated how revisions is affected by two automatic ARIMA model selection methods (automdl and pickmdl). Furthermore, it is shown that straightforward re-identification of outliers (the concurrent method) leads to big revisions. From this knowledge the second part of the paper considers the problem of automatically dealing with outliers (Langsrud, 2012). How should potential outliers be handled before the final decision is made? Three algorithms are suggested which can be named as “jump in and out”, “jump in” and “jump out”. It is demonstrated how revisions and out-of-sample forecasts (quality of model) are affected by using the algorithms. The results are compared to the concurrent method. The results indicate, however, that the best improvements are obtained by increasing the outlier detection limit. The analyses were made by running X-12-ARIMA via the R programming language

Genome-wide levels of variation in space and time in Scandinavian subpopulations of the arctic fox (Vulpes lagopus)

Bruk av genom-skalert data åpner opp for nye muligheter angående genomiske spørsmål om bevaring. For eksempel har konserverings genetikk og genomikk vist seg å være viktig innen bevaring og overvåkning av truede arter. Den Skandinaviske fjellreven (Vulpes lagopus) er intet unntak. Populasjonen opplevde en rask nedgang i populasjonsstørrelsen på begynnelsen av 1900-tallet. Dessverre klarte ikke populasjonen å komme seg, som følge av lav mattilgjengelighet (dvs. ustabile gnagersykluser) og interspesifikk konkurranse og predasjon fra rødreven (Vulpes vulpes). I tillegg vil en liten populasjonsstørrelse og en fragmentert struktur hos den Skandinaviske fjellreven i seg selv bidra til at subpopulasjoner finner seg i en høy risiko for å oppleve genetisk drift og innavlsdepresjon. Det har derfor i løpet av de siste tiårene blitt iverksatt flere bevaring og forvaltningstiltak i Sverige og Norge. Formålet med iverksettingen var først og fremst å forbedre forholdene og øke antallet fjellrev i Skandinavia, dernest å gjenopprette subpopulasjoner hvor fjellreven var utryddet og støtte eksisterende subpopulasjoner. Formålet i dette studiet er å sammenligne genotype data med høy tetthet for individer i 6 fjellrev subpopulasjoner i Skandinavia, for å undersøke den genetiske variasjonen innen og mellom subpopulasjonen, over hele og regionalt i fjellrev genomet. En Affymetrix Axiom 702K SNP-array tilpasset fjellrev og rødrev ble brukt til å genotype individene. Studiets resultater antyder at den genetiske variasjonen (dvs. heterozygositet) innen hver subpopulasjon har for det meste økt over studiets omfang. Tilsvarende har det vært en endring i den genetiske sammensetningen for de fleste subpopulasjonene gjennom studieperioden, som vist av observerte nivåer av genetisk differensiering på tvers av hele og/eller deler av genomet mellom sampling perioder for subpopulasjonene. Resultatene indikerer også at den genetiske differensieringen mellom subpopulasjoner (over eller innen genomet) har generelt avtatt gjennom studieperioden. Videre studier med lengre tidsperioder, kan ved å bruke liknende tilnærminger som dette studiet, avdekke hvordan genetisk drift, migrasjon (gen flyt) og seleksjon samhandler i å forme variasjon innen regioner og på tvers av hele genomet, og dermed kunne trekke konklusjoner om genetiske konsekvenser av pågående bevaringsaksjoner. Dette studiet viser at genotype data (genom-bredt) med stor tetthet, i kombinasjon med et fjellrev-referanse-genom, åpner opp for nye muligheter innen konserverings genomikk og relaterte spørsmål for den Skandinaviske fjellreven.Use of genome-scale genetic data opens up new possibilities for looking into important questions in conservation biology. For example, conservation genetics and genomics has proven to be especially important in preservation and monitoring of threatened species. The Scandinavian arctic fox (Vulpes lagopus) is no exception. The population experienced a rapid decline in population size in the beginning of the 20th century. Unfortunately, the population was not able to recover, following low food availability (i.e. unstable rodent cycles) and interspecific competition and predation from the red fox (Vulpes Vulpes). In addition, the small size and fragmented structure of the Scandinavian arctic fox population in itself contributed to making the subpopulations having high risk of experiencing genetic drift and inbreeding depression. Over the last decades, several conservation and management measures have been implemented in both Sweden and Norway. The purpose was primarily to improve conditions and increase the number of arctic foxes in Scandinavia, and second, to restore subpopulations where the arctic fox had gone extinct and support existing subpopulations. In this study the aim is to compare high-density genotype data for individuals in 6 subpopulations of the arctic fox in Scandinavia, to investigate the genetic variation within and between subpopulations, all over and regionally in the arctic fox genome. A custom Affymetrix Axiom 702K SNP-array for arctic fox and red fox was used to genotype the individuals. The results of this study suggest that the genetic variation (i.e. heterozygosity) within each subpopulation, for the most part, has increased over the study period. Accordingly, there has been a change in the genetic composition of most subpopulations during the study period, as shown by the observed levels of genetic differentiation across the whole and/or parts of the genome between sampling periods for the subpopulations. The results also indicate that the genome-wide and/or regional (within the genome) genetic differentiation between subpopulations has generally declined through the study period. Further studies with longer time periods using approaches similar to the ones in this study may be able to reveal how genetic drift, migration (gene flow) and selection interact to shape the variation within regions and across the whole genome, and thus make it possible to draw conclusions about genetic consequences of on-going conservation management actions. This study shows that high-density genome-wide genotype data, in combination with an arctic fox reference genome, open up new possibilities within conservation genomics and related questions for the Scandinavian arctic fox

Inferring the learning rule from spike train data with particle Metropolis-Hastings

Hjernen vår består av nerveceller som kommuniserer med hverandre ved å sende elektriske impulser gjennom bindinger. Forskning har vist at disse bindingene kan utvikle seg over tid, og at måten disse utvikler seg på ser ut til å følge noen underliggende regler, som vi referer til som «læringsregler». Disse er essensielle for læring og hukommelse. Statistiske metoder for å bestemme den underliggende læringsreglen i data fra nervecelleaktivitet kan dermed gi viktig innsikt. Denne masteroppgaven beskriver partikkel Metropolis-Hastings for å karakterisere læringsregelen i simulert data for en synapse. Denne metoden er inspirert av (Linderman et al., 2014). I denne oppgaven brukte vi «spike-timing dependent plasticity»-læringsreglen, og utførte statistisk inferens av parameterne i denne. Nervecelleaktiviteten ble modellert som en Bernoulliprosess. De numeriske eksperimentene viste at med tilstrekkelig data og lite nok støy, kunne informasjon om parameterne i læringsregelen bestemmes fra dataen.The brain is a system of connected neurons that communicate by transmitting electrical signals to each other. Research has revealed that the way in which neural connections develop over time seem to follow some underlying patterns. These are known as learning rules, and are essential for the brain to learn and form memories. Statistical methods for inferring the learning rule from recordings of neural activity may thus give insights on basic computationally principles in different brain areas. Furthermore it has been hypothesized that the learning rule might be disturbed by memory related diseases, such as Alzheimer’s. Therefore, being able to detect the underlying learning rule could shed light on the origin and workings of Alzheimer’s disease and even have applications in medical research as well. This thesis covers the implementation of particle Metropolis-Hastings for characterizing the learning rule in simulated neural spike data for one synapse, inspired by the method proposed in (Linderman et al., 2014). For our purpose we used the additive spike-timingdependent plasticity (STDP) learning rule, and aimed at inferring its learning rule parameters. The neural spiking was modeled as a Bernoulli process in the Generalized Linear Model (GLM) framework. By numerical experiments it was demonstrated that with enough data and sufficiently low noise level, information of the learning rule parameters could be reconstructed from the spike data by using this method. The results indicate that it could be possible to distinguish between learning rules, by analysing spike train data with particle Metropolis-Hastings

Sleep at night and patients’ behaviours the next day in a catchment-area-based psychiatric hospital

This thesis explores the associations between sleep at night and behaviour the next day in two patient samples from a defined catchment area admitted to the Department of Psychiatry, St Olav’s University Hospital: outpatients with delayed sleep-wake phase disorder (DSWPD) admitted to the specialist clinic for patients with sleep disorders, and inpatients acutely admitted to the psychiatric intensive care units (PICUs). Sleep is an essential function for all animals, including humans. Disruption of sleep patterns and lack of sleep affect our functioning and behaviour. Lack of sleep has numerous effects, ranging from deterioration in performance on more complicated cognitive tasks to being associated to a number of somatic health problems, such as increased weight, diabetes, and decreased life expectancy. The associations between sleep and daytime functioning are complex and bidirectional. Among outpatients with DSWPD and acute psychiatric inpatients admitted to PICUs, disturbed sleep and challenging behaviour is common. The impact of sleep disruptions on behaviour the next day is seldom studied. This thesis aimed to study the awakening threshold and changes in cognitive function after awakening in DSWPD patients. Additionally to study the effects of sleep duration or night-tonight variations in sleep duration on length of stay and observer-rated aggressive behaviours in acutely admitted psychiatric patients, and finally to investigate whether the predictive properties of a violence risk instrument predicted aggressive incidents more precisely if a sleep variable was added to it. Methods Paper one reports data from nine patients with DSWPD and nine sex- and age-matched healthy controls who stayed in the sleep laboratory for one night. They were examined with polysomnography and completed the continuous performance test (CPT) in the afternoon and immediately upon waking. An alarm clock was activated at 07:00 with sound intensity increasing from 72 to 104 dB. Paper two reports data from 135 patients consecutively admitted to a PICU. Papers three and four report data for 50 of these admissions. The nurses registered the time the patients were sleeping, aggressive behaviours using the Brøset Violence Checklist (BVC), and aggressive incidents using the Staff Observation Aggression Scale-Revised (SOAS-R). Results In all patient groups we found wide variability in sleep duration between individuals. Three of the patients with DSWPD did not wake up at the alarm sound of 104 dB. The three patients were in rapid eye movement (REM) sleep. On the CPT test, patients with DSWPD had longer reaction times in the morning than in the afternoon. In the acutely admitted subgroup of patients with schizophrenia, sleep duration the first night correlated negatively with the length of stay. For the whole group of patients, the difference in sleep duration from night one to night two were correlated with length of stay. Short sleep duration the first night correlated with aggressive behaviour the next day. During the stay, large absolute differences in sleep duration between two consecutive nights correlated withaggressive behaviour the next day, and short sleep duration was associated with violent incidents. The violence risk instrument BVC appeared to predict aggressive incidents more precisely when a sleep variable was added. Discussion We found that patients with DSWPD struggle to wake up with an alarm clock. These patients were in a period of REM sleep, rather than in the expected period of slow wave sleep (SWS). Their reported drowsiness in the morning was supported by a neuropsychological test. Among the acute psychiatric patients in the PICUs, we found large variations in sleep duration between individual patients, as well as large intra-individual lack of stability in sleep duration. The lack of stability in sleep duration, and the magnitude of the night-to-night variations of the first nights predicted the length of stay in the PICU. These factors were also associated with threatening behaviour and aggressive incidents. Assessments of sleep disorders may increase the value of psychometric instruments designed to predict the imminent risk of violence in psychiatric inpatients. The studies had a limited number of participants. There were also limitations in the designs and measures used. Thus, the results should be interpreted with caution. The two-process model theory of sleep regulation may be useful when comparing studies, interpreting results and seeking new treatmentsdigital fulltext is not avialabl

An environmentally benign antimicrobial nanoparticle based on a silver-infused lignin core

Silver nanoparticles have antibacterial properties, but their use has been a cause for concern because they persist in the environment. Here, we show that lignin nanoparticles infused with silver ions and coated with a cationic polyelectrolyte layer form a biodegradable and green alternative to silver nanoparticles. The polyelectrolyte layer promotes the adhesion of the particles to bacterial cell membranes and, together with silver ions, can kill a broad spectrum of bacteria, including Escherichia coli, Pseudomonas aeruginosa and quaternary-amine-resistant Ralstonia sp. Ion depletion studies have shown that the bioactivity of these nanoparticles is time-limited because of the desorption of silver ions. High-throughput bioactivity screening did not reveal increased toxicity of the particles when compared to an equivalent mass of metallic silver nanoparticles or silver nitrate solution. Our results demonstrate that the application of green chemistry principles may allow the synthesis of nanoparticles with biodegradable cores that have higher antimicrobial activity and smaller environmental impact than metallic silver nanoparticles

Crossing the Gould Belt in the Orion vicinity

We present a study of the large-scale spatial distribution of 6482 RASS X-ray sources in approximately 5000 deg^2 in the direction of Orion. We examine the astrophysical properties of a sub-sample of ~100 optical counterparts, using optical spectroscopy. This sub-sample is used to investigate the space density of the RASS young star candidates by comparing X-ray number counts with Galactic model predictions. We characterize the observed sub-sample in terms of spectral type, lithium content, radial and rotational velocities, as well as iron abundance. A population synthesis model is then applied to analyze the stellar content of the RASS in the studied area. We find that stars associated with the Orion star-forming region do show a high lithium content. A population of late-type stars with lithium equivalent widths larger than Pleiades stars of the same spectral type (hence younger than ~70-100 Myr) is found widely spread over the studied area. Two new young stellar aggregates, namely "X-ray Clump 0534+22" (age~2-10 Myr) and "X-ray Clump 0430-08" (age~2-20 Myr), are also identified. The spectroscopic follow-up and comparison with Galactic model predictions reveal that the X-ray selected stellar population in the direction of Orion is characterized by three distinct components, namely the clustered, the young dispersed, and the widespread field populations. The clustered population is mainly associated with regions of recent or ongoing star formation and correlates spatially with molecular clouds. The dispersed young population follows a broad lane apparently coinciding spatially with the Gould Belt, while the widespread population consists primarily of active field stars older than 100 Myr. We expect the "bi-dimensional" picture emerging from this study to grow in depth as soon as the distance and the kinematics of the studied sources will become available from the future Gaia mission.Comment: 17 pages, 13 figures, 4 tables. Accepted for publication in Astronomy and Astrophysics. Abstract shortene

Estimating the Carbon Footprint of Norway's Food Consumption: The Impact of Domestically Produced vs. Imported Food

Tiltak for å redusere klimaavtrykket i de globale matsystemene er avgjørende for å begrense global oppvarming. Den norske regjeringen har lagt vekt på at utslipp fra matproduksjon i landbrukssektoren må gå ned for å lette det totale karbonfotavtrykket i Norge. Samtidig har de et mål om å øke selvforsyningen. Ettersom selvforsyningsgraden påvirker karbonfotavtrykket og omvendt, er det nødvendig å se disse målene i sammenheng. Dette krever detaljert kunnskap om utslippene fra både norsk matproduksjon og importerte råvarer. Hovedmålet i denne studien var å kvantifisere klimapåvirkningen (fra vugge til gårdsport) av all mat som produseres til norsk konsum. En ny metode ble utviklet for å estimere matforsyning basert på produksjonsland og matvaregruppe. Dette ble kombinert med resultater fra livssyklusanalyser av matprodukter for å beregne den totale klimapåvirkningen av norskprodusert og importert mat adskilt, fordelt på ulike matvaregrupper. Studien hadde i tillegg et mål om å undersøke sammenhengen mellom selvforsyningsgraden og klimapåvirkningen av mat, samt identifisere nøkkelstrategier for å begrense klimafotavtrykket av det norske matbehovet. Studien viser at norskprodusert mat har en høyere klimapåvirkning enn importert mat. Dette var også tilfelle for konstruerte scenarioer der matbehovet knyttet til den nåværende norske dietten ble dekt av enten norsk produksjon eller import. Oppbygningen av selve dietten viser seg likevel å ha større påvirkning på det totale klimafotavtrykket fra mat, enn hvorvidt maten er produsert innenlands eller utenlands. Ettersom animalbaserte matvarer står for hovedandelen av klimapåvirkningen, er et viktig utslippsreduserende tiltak å gå over til et mer plantebasert kosthold. Siden den nåværende matproduksjonen i Norge i stor grad belager seg på husdyrproduksjon, er dette spesielt utfordrende med tanke på det parallelle målet om å øke selvforsyningsgraden. I tillegg viser resultatene at plantebasert mat generelt er mer utslippsintensivt i Norge enn utenlands. Disse funnene impliserer at norsk matproduksjon må gjennomgå drastiske endringer for å redusere karbonfotavtrykket av Norges matbehov uten å minke selvforsyningsgraden.Mitigation efforts within the global food systems are crucial to limit global warming. The Norwegian Government has emphasized that the emissions from the agri-food sector must be reduced to lessen Norway's total carbon footprint. Simultaneously, they aim to increase self-sufficiency. Since the self-sufficiency rate affects the carbon footprint of food and vice versa, these two goals should be considered together. This requires detailed knowledge about the emissions caused by domestically produced and imported food. The main objective of this study was to quantify the climate impact (cradle-to-farm gate) of all food production covering Norway’s consumption. A novel method was developed to estimate the food supply based on the producer country and food category. This was used in unison with results from life cycle assessments of food products to obtain the total climate impact for domestically produced food and imports separately, further divided into food categories. In addition, the study aimed to investigate the relationship between self-sufficiency and the climate impact of food, and to identify key climate change mitigation strategies for the Norwegian food demand. The study shows that domestically produced food has a larger climate impact than imported food. This also applied to the constructed scenarios where the food demand caused by the current Norwegian diet is covered by only domestic production or imports. However, dietary patterns are found to have a larger influence on the climate impact of food than the self-sufficiency rate. Animal-based products account for the dominant share of total impact, indicating that a crucial climate change mitigation strategy is to reduce animal-based food consumption. Since the current domestic food production relies heavily on livestock, this is particularly challenging, considering the goal of increasing self-sufficiency. Additionally, the results show that plant-based food is more emission-intensive in domestic production than imports. Consequently, the findings imply that domestic food production must undergo drastic changes to reduce the carbon footprint of Norway’s food demand without lowering self-sufficiency

Estimating the Carbon Footprint of Norway's Food Consumption: The Impact of Domestically Produced vs. Imported Food

Tiltak for å redusere klimaavtrykket i de globale matsystemene er avgjørende for å begrense global oppvarming. Den norske regjeringen har lagt vekt på at utslipp fra matproduksjon i landbrukssektoren må gå ned for å lette det totale karbonfotavtrykket i Norge. Samtidig har de et mål om å øke selvforsyningen. Ettersom selvforsyningsgraden påvirker karbonfotavtrykket og omvendt, er det nødvendig å se disse målene i sammenheng. Dette krever detaljert kunnskap om utslippene fra både norsk matproduksjon og importerte råvarer. Hovedmålet i denne studien var å kvantifisere klimapåvirkningen (fra vugge til gårdsport) av all mat som produseres til norsk konsum. En ny metode ble utviklet for å estimere matforsyning basert på produksjonsland og matvaregruppe. Dette ble kombinert med resultater fra livssyklusanalyser av matprodukter for å beregne den totale klimapåvirkningen av norskprodusert og importert mat adskilt, fordelt på ulike matvaregrupper. Studien hadde i tillegg et mål om å undersøke sammenhengen mellom selvforsyningsgraden og klimapåvirkningen av mat, samt identifisere nøkkelstrategier for å begrense klimafotavtrykket av det norske matbehovet. Studien viser at norskprodusert mat har en høyere klimapåvirkning enn importert mat. Dette var også tilfelle for konstruerte scenarioer der matbehovet knyttet til den nåværende norske dietten ble dekt av enten norsk produksjon eller import. Oppbygningen av selve dietten viser seg likevel å ha større påvirkning på det totale klimafotavtrykket fra mat, enn hvorvidt maten er produsert innenlands eller utenlands. Ettersom animalbaserte matvarer står for hovedandelen av klimapåvirkningen, er et viktig utslippsreduserende tiltak å gå over til et mer plantebasert kosthold. Siden den nåværende matproduksjonen i Norge i stor grad belager seg på husdyrproduksjon, er dette spesielt utfordrende med tanke på det parallelle målet om å øke selvforsyningsgraden. I tillegg viser resultatene at plantebasert mat generelt er mer utslippsintensivt i Norge enn utenlands. Disse funnene impliserer at norsk matproduksjon må gjennomgå drastiske endringer for å redusere karbonfotavtrykket av Norges matbehov uten å minke selvforsyningsgraden.Mitigation efforts within the global food systems are crucial to limit global warming. The Norwegian Government has emphasized that the emissions from the agri-food sector must be reduced to lessen Norway's total carbon footprint. Simultaneously, they aim to increase self-sufficiency. Since the self-sufficiency rate affects the carbon footprint of food and vice versa, these two goals should be considered together. This requires detailed knowledge about the emissions caused by domestically produced and imported food. The main objective of this study was to quantify the climate impact (cradle-to-farm gate) of all food production covering Norway's consumption. A novel method was developed to estimate the food supply based on the producer country and food category. This was used in unison with results from life cycle assessments of food products to obtain the total climate impact for domestically produced food and imports separately, further divided into food categories. In addition, the study aimed to investigate the relationship between self-sufficiency and the climate impact of food, and to identify key climate change mitigation strategies for the Norwegian food demand. The study shows that domestically produced food has a larger climate impact than imported food. This also applied to the constructed scenarios where the food demand caused by the current Norwegian diet is covered by only domestic production or imports. However, dietary patterns are found to have a larger influence on the climate impact of food than the self-sufficiency rate. Animal-based products account for the dominant share of total impact, indicating that a crucial climate change mitigation strategy is to reduce animal-based food consumption. Since the current domestic food production relies heavily on livestock, this is particularly challenging, considering the goal of increasing self-sufficiency. Additionally, the results show that plant-based food is more emission-intensive in domestic production than imports. Consequently, the findings imply that domestic food production must undergo drastic changes to reduce the carbon footprint of Norway's food demand without lowering self-sufficiency