A dummy variable (also known as indicator variable) is a numeric variable that indicates the presence or absence of some level of a categorical variable. The word "dummy" does not imply that these variables are not smart. Rather, dummy variables serve as a substitute or a proxy for a categorical
Don’t get me wrong. I have no doubt in the capabilities of our SAS products and SAS solutions! But I wanted to get a firsthand experience of our new solution for text analytics, SAS Contextual Analysis 14.1. And the result is very convincing! But let’s start from the beginning. Functions
Many simulation and resampling tasks use one of four sampling methods. When you draw a random sample from a population, you can sample with or without replacement. At the same time, all individuals in the population might have equal probability of being selected, or some individuals might be more likely
How do you sample with replacement in SAS when the probability of choosing each observation varies? I was asked this question recently. The programmer thought he could use PROC SURVEYSELECT to generate the samples, but he wasn't sure which sampling technique he should use to sample with unequal probability. This
I began 2016 by compiling a list of popular articles from my blog in 2015. This "People's Choice" list contains many interesting articles, but some of my personal favorites did not make the list. Today I present the "Editor's Choice" list of articles that deserve a second look. I've grouped
I wrote 114 posts for The DO Loop blog in 2015. Which were the most popular with readers? In general, highly technical articles appeal to only a small group of readers, whereas less technical articles appeal to a larger audience. Consequently, many of my popular articles were related to data
Beim adventlichen Weihnachtsstern Basteln am vierten Advent hob ich schon warnend den Finger und hielt Sie gemäß des Mottos „Save a Tree“ dazu an, beim Ausdruck der Schnittmuster mit dem Papier ressourcenschonend umzugehen. Vor dem Hintergrund der in Paris erfolgreich verhandelten Begrenzungen des zukünftigen CO2-Ausstoßes, muss man sich ja auch noch
Der letzte Tag vor Heiligabend! Die Farbe an ein paar wenigen Geschenken trocknet noch, die letzten Geschenke werden verpackt und die letzten Schleifen gebunden. Ein letztes Mal setzt sich das Christkind mit seinen Auslieferungs-Engeln zusammen. Wird das Wetter mitspielen? Unsere bisherigen Themen: Business Analytics allgemein (1), Vergangenes analysieren – Künftiges
Heute müssen sich die Engel die Routenplanung vornehmen. Schließlich hat das Christkind nur wenige Stunden Zeit. Nimmt es auf dem Weg von Familie Minstrel zu Familie Spillner lieber die Mozart-oder doch lieber die Beethovenstraße? Fährt es überhaupt direkt nach Familie Mustermann zu Familie Spillner oder ist es vielleicht sinnvoll, zwischendrin
Year-end outlooks from most analysts project the low-price environment in the oil market will continue for most of next year, but some pundits emphasize that the market has bottomed out and suggest recovery, though gradual, may be seen if increasing demand outpaces supply growth and sops up some of the
A SAS customer asked: Why isn't the chi-square distribution supported in PROC UNIVARIATE? That is an excellent question. I remember asking a similar question when I first started learning SAS. In addition to the chi-square distribution, I wondered why the UNIVARIATE procedure does not support the F distribution. These are
Times have changed. As the oil industry shutters and sheds investments that made sense during the two-year period in which oil rode comfortably above $90, the market is establishing a new equilibrium at $40/barrel. This despite the fact that the Baker Hughes domestic rig count is down 64 percent. It’s
The INFORMS 2015 Annual Meeting will be held in Philadelphia November 1-4. More than two dozen SAS staff will participate, and SAS will have three adjacent booths representing SAS/OR (and all of Advanced Analytics), JMP, and the SAS Global Academic Program. SAS is well-represented among the presentations at this meeting,
Erfahrungen aus einem Selbstversuch mit SAS Contextual Analysis Bitte verstehen Sie mich nicht falsch. Ich bin unseren SAS Produkten und SAS Lösungen gegenüber in keinster Weise misstrauisch! Trotzdem wollte ich die Möglichkeiten unserer neuen Lösung für Text Analytics „SAS Contextual Analysis 14.1“ auf der eigenen Haut spüren und verstehen lernen.
IFRS 9 und Stresstesting: Zwei aktuelle Themen, dem ersten Gedanken nach in verschiedenen Unternehmensbereichen angesiedelt und doch gibt es große Überschneidungen … IFRS 9 als Teil des Rechnungswesen und Risikomanagements Die Vorschriften von IFRS 9 zur Erfassung von Wertminderungen basieren auf dem Expected-Credit-Loss-Modell, d.h. einem Modell zukünftig erwarteter Forderungsausfälle. Diese
Big data is here to stay, whether we like it or not. Regardless of how you feel about it, it can help solve problems which simply could not be addressed without big data and advanced analytics. One area in which big data and analytics can provide huge benefits is the medical arena. In a recent
Though crude oil prices edged up last week, the market remains well below VirtualOil’s original $50 strike price, meaning the hypothetical portfolio’s production is shut in in the spot market again. Oversupply continues while China GDP forecasted growth is slowing. Given the market outlook, the VirtualOil board has decided to
In a recent meeting, the CIO of a leading commercial automotive company’s shared his experience of high complexity in managing forecasting data. I was not surprised. Often demand planners complain about managing forecasting data. I can relate to where there are coming from. It’s due to the approach prescribed by their legacy
A Vermont Department of Children Families (DCF) worker was murdered last month. The lead suspect is the mother of a child that was previously removed from her care and placed in foster care. This tragedy illustrates the challenges and risks that workers have in the field of serving at risk
SAS/OR 14.1, which became available on July 14, delivers a number of new and enhanced features in optimization and simulation. These changes are designed to make SAS/OR even easier to use and to enable you to model and solve larger, more complex problems more efficiently. If you're using SAS/OR now,
You may not be in London on October 7 to take advantage of the Lancaster Centre for Forecasting's free workshop on promotional forecasting. However, there are still plenty of forecasting educational opportunities coming up this fall: SAS Business Knowledge Series Best Practices in Demand-Driven Forecasting (Chicago, September 24-25) My colleague
Last month I wrote about how to simulate a drunkard's walk in SAS for a drunkard who can move only left or right in one direction. A reader asked whether the problem could be generalized to two dimensions. Yes! This article shows how to simulate a 2-D drunkard's walk, also
We are all modelers. Whenever you plan, you are building a model. Whenever you imagine, you are building a model. When you create, write, paint or speak, you first build in your head a model of what you want to accomplish, and then fill in the details with words, movements
During a lighthearted moment in a serious conversation, Howard Schmidt, cyber security advisor to multiple presidents, told a Wall Street Journal interviewer that relying on a government agency as your primary backstop during a major cyber security breach is akin to calling Ghostbusters: you might not get the help you
Wären Sie in der Lage, rechtzeitig auf Sicherheitslücken in Ihrem Unternehmen zu reagieren, sei es in der Produktion oder in der IT, auch wenn es Made in Germany hieße? Könnten Sie Ausfälle oder Qualitätsprobleme frühzeitig erkennen? Wie sähe es aus, wenn Sie feststellen würden, dass Ihre Kunden nicht mehr mit
The triangular distribution has applications in risk analysis and reliability analysis. It is also a useful theoretical tool because of its simplicity. Its density function is piecewise linear. The standardized distribution is defined on [0,1] and has one parameter, 0 ≤ c ≤ 1, which determines the peak of the
SAS Global Forum では、毎年SASの全てのキーマンが集結します。もちろん2015も例外ではありませんでした。2014年にスマートメーター活用セミナーの講師として来日もした、グローバルセールス＆開発マネージメント ビジネスディレクターのTim Fairchildおよび、エネルギーソリューション担当プロダクトマーケティングマネージャーのAlyssa Farrellと短い朝食ミーティングで意見交換をしてきました。日本では電力小売り自由化もありアナリティクスの活用が進んでいますが、世界的に見てもエネルギー業界にアナリティクスの大きな潮流がやってきています。 それを表すかのように、SAS Global Forum 2015において非常に多くのユーティリティ業界に関するプレゼンテーションがありました。それをご紹介します。 生存時間分析を使用した変圧器の寿命予測とSAS Enterprise Minerを使用した過負荷状態で変圧器を使用している際のリスクモデリング（Predicting transformer lifetime using survival analysis and modeling risk associated with overloaded transformers Using SAS® Enterprise MinerTM 12.1） 「いつ変圧器が故障するのか？」 これが米国のユーティリティ企業が毎日頭を悩ませている問題である。ユーティリティ企業のインフラで最も重要なものの一つが変圧器である。コストを削減し計画的にメンテナンスし、故障による損失を低減するためには、この変圧器の寿命を把握することが重要である。そしてもう一つ重要なことは、過負荷による突発的なパフォーマンスダウンを避けるために高リスクな変圧器を事前に特定しメンテナンスすることである。この論文の目的は、SASを使用して変圧器の寿命を予測し、それらの故障に繋がる様々な要因を特定し、メンテナンスを効率的に行うために変圧器を、負荷状態に基づいて、高リスク、中リスクそして小リスクといったカテゴリに分類するモデルを作成することである。この研究で使用したデータは、米国のユーティリティ企業のものであり、2006年から2013年までのデータである。このデータに対して生存時間分析を行った。Cox回帰分析（比例ハザードモデル）を使用して、変圧器の故障の要因を特定した。また負荷に応じたリスクカテゴリを作成するために、いくつかのリスクベースモデルを使用した。（続きはこちら） 顧客クラスタリングにおけるイノベーティブな方法(An Innovative Method of Customer Clustering) この論文は、SASを使用して顧客セグメントを作成する新しい方法について紹介する。著者はある巨大なユーティリティ企業が提供している９つのプログラムに登録している顧客を調査した。これらにプログラムとは、請求の平準化、支払方法、再生可能エネルギー、効率化、機器の保護、使用量レポートなどである。640,788の家庭のうち、374,441のデータが利用可能であった。これら約半数（49.8%）の分析対象顧客はいくつかのタイプのプログラムに属しており、顧客の特徴を通してこれらプログラムの間の共通性を見出すためには、多くの場合、クラスター分析と相関マトリックスが利用される。しかし、所属しているか否かという二値という性質により、これらの手法の価値はかなり限定的になる。それだけでなく、各プログラムは相互に排他的であることもその一因となる。これらの制限を乗り越えるために、各顧客がどのプログラムに属するかの予測スコアを算出するために、PROC LOGISTICを使用した。（続きはこちら） ブラジルの電力部門における電力損失の査察のためのターゲット選定の改善のためのモデリング－CEMIGの事例(Modeling to improve the customer unit target selection for inspections of
You've probably heard of a random walk, but have you heard about the drunkard's walk? I've previously written about how to simulate a one-dimensional random walk in SAS. In the random walk, you imagine a person who takes a series of steps where the step size and direction is a
Within the SAS DATA step, the LAG function is provided to return a variable’s value from a previous data set observation. With certain data criteria, sometimes there is a need to look ahead at the next observation and you would expect to use a LEAD function, but this does not
I previously wrote about the best way to suppress output from SAS procedures. Suppressing output is necessary in simulation and bootstrap analyses, and it is useful in other contexts as well. In my previous article, I wrote, "many programmers use ODS _ALL_ CLOSE as a way to suppress output, but
