- Italiana Terni - Blogger
- Cartão forex on-line Açailândia
- Troca de divisas on-line Belém: Bandas de bollinger e ...
- Online Courses - Learn Anything, On Your Schedule Udemy
- Objective English By Hari Mohan Prasad Ebook3000
- Forex el zulia
- Trading Marche
- Blog de 123votez.com - Sondages - Commentaires
- Opciones Binarias arauca: 2017
- Guide Binära val Fagersta

Hi guys, somebody knows if there's an equivalence of the next function from Stata in R:

In stata after running the MCA command i can use the predict command like this:

MCA var1 var2 predict var3 if e(sample)

In R i have been trying the next:

MCA1 <- MCA(df, var1, var2) predict.mca(MCA1, df)

But I don't get the same results that i get from Stata Somebody knows how I can emulate the e(sample) function?

Thanks a lot

submitted by maxkomh to rstats [link] [comments]
In stata after running the MCA command i can use the predict command like this:

MCA var1 var2 predict var3 if e(sample)

In R i have been trying the next:

MCA1 <- MCA(df, var1, var2) predict.mca(MCA1, df)

But I don't get the same results that i get from Stata Somebody knows how I can emulate the e(sample) function?

Thanks a lot

submitted by murchie85 to pygame [link] [comments]

submitted by pionutbz to u/pionutbz [link] [comments] |

I know the js math module has it, but can I just write javascript in the formula field?

submitted by actopozipc to RPGMaker [link] [comments]
submitted by TheCanadianVending to vexillologycirclejerk [link] [comments] |

I have two columns, one of "Months" (1999m1, 1999m2, 1999m3, etc) and another of "Events" which indicate whether an event occurred which month it corresponded with (0,0,0,1,0,0).

My goal is to define a two-year event window, and a three-year window, meaning, I want to flag the rows that have the event-time variable, between -24 and 23, or -36 and 35. This is with the final goal of creating a buffer that returns positive (0) or negative (1) whether there is another event that exists within that buffer.

How can I do this in STATA?

submitted by bidibidi_bombom to stata [link] [comments]
My goal is to define a two-year event window, and a three-year window, meaning, I want to flag the rows that have the event-time variable, between -24 and 23, or -36 and 35. This is with the final goal of creating a buffer that returns positive (0) or negative (1) whether there is another event that exists within that buffer.

How can I do this in STATA?

Can't figure out an equivalent function to "lincom" command in R ?Hence cannot really calculate p- values.If at all someone can help me with which stat-test to use to calculate p-values ?Variables -disease = numeric =0,1race= char= European, Indian, AsianAge1=num= 0,1sex =factor= M,F

submitted by afg-6780 to stata [link] [comments]
glm disease i.raceage1 sex, link(identity) family(binomial) testparm X di "Omnibus test of age1race interaction p = " %8.6f r(p) lincom age1 di %6.4f r(p) " | | " lincom age1 + _IraceXage1__i' di %6.4f r(p) " | " _continue lincom _IraceXage__i' di %6.4f r(p) " | "So far, in R have reached till here any help would be appreciated -

model1<-glm(formula = disease ~ race * age1 + sex, family = binomial(link = "identity"), data = MORT) summary(model1) fit2<-augment (model1, newdata = MORT, type.predict = "response") fit2$.fitted<- fit2$.fitted*100 install.packages("remotes") remotes::install_github("bmckuw/UWbe536")library(UWbe536) lincom(model1, lc = "age1 == 0") lincom(model1, lc = "race+age1 = 0")

I have a question concerning the coefficients in the two programs, when estimating a proportional hazard model with a Weibull baseline hazard function.

When using the same dataset i get different coefficients, but almost identical p-values and standard errors.

Actually, the signs of the coefficients are exactly opposite across the two programs, which can have quite the consequences, if you want to conclude anything.

I am using it for my bachelor thesis on costumer churn, so instead of uploading manipulated results and data, I have found two videos on Youtube, which does exactly the same with identical data and still gets opposite results.

Can someone please help?

Link R: https://www.youtube.com/watch?v=qt2ufTPCWwI Link STATA: https://www.youtube.com/watch?v=jg7laENsXSQ She introduces parametric estimation arount 12 minutes in both.

submitted by Kolminator to stata [link] [comments]
When using the same dataset i get different coefficients, but almost identical p-values and standard errors.

Actually, the signs of the coefficients are exactly opposite across the two programs, which can have quite the consequences, if you want to conclude anything.

I am using it for my bachelor thesis on costumer churn, so instead of uploading manipulated results and data, I have found two videos on Youtube, which does exactly the same with identical data and still gets opposite results.

Can someone please help?

Link R: https://www.youtube.com/watch?v=qt2ufTPCWwI Link STATA: https://www.youtube.com/watch?v=jg7laENsXSQ She introduces parametric estimation arount 12 minutes in both.

Can't figure out an equivalent function to "lincom" command in R ?

Hence cannot really calculate p- values.

If at all someone can help me with which stat-test to use to calculate p-values ?

Variables -

disease = numeric =0,1

race= char= European, Indian, Asian

Age1=num= 0,1

sex =factor= M,F

submitted by afg-6780 to RStudio [link] [comments]
Hence cannot really calculate p- values.

If at all someone can help me with which stat-test to use to calculate p-values ?

Variables -

disease = numeric =0,1

race= char= European, Indian, Asian

Age1=num= 0,1

sex =factor= M,F

glm disease i.raceage1 sex, link(identity) family(binomial) testparm X di "Omnibus test of age1race interaction p = " %8.6f r(p) lincom age1 di %6.4f r(p) " | | " lincom age1 + _IraceXage1__i' di %6.4f r(p) " | " _continue lincom _IraceXage__i' di %6.4f r(p) " | "So far, in R have reached till here any help would be appreciated -

model1<-glm(formula = disease ~ race * age1 + sex, family = binomial(link = "identity"), data = MORT) summary(model1) fit2<-augment (model1, newdata = MORT, type.predict = "response") fit2$.fitted<- fit2$.fitted*100 install.packages("remotes") remotes:: install_github("bmckuw/UWbe536")library(UWbe536) lincom(model1, lc = "age1 == 0") lincom(model1, lc = "race+age1 = 0")

I have a question concerning the coefficients in the two programs, when estimating a proportional hazard model with a Weibull baseline hazard function.

When using the same dataset i get different coefficients, but almost identical p-values and standard errors.

Actually, the signs of the coefficients are exactly opposite across the two programs, which can have quite the consequences, if you want to conclude anything.

I am using it for my bachelor thesis on costumer churn, so instead of uploading manipulated results and data, I have found two videos on Youtube, which does exactly the same with identical data and still gets opposite results.

Can someone please help?

Link R: https://www.youtube.com/watch?v=qt2ufTPCWwI Link STATA: https://www.youtube.com/watch?v=jg7laENsXSQ She introduces parametric estimation arount 12 minutes in both.

submitted by Kolminator to rstats [link] [comments]
When using the same dataset i get different coefficients, but almost identical p-values and standard errors.

Actually, the signs of the coefficients are exactly opposite across the two programs, which can have quite the consequences, if you want to conclude anything.

I am using it for my bachelor thesis on costumer churn, so instead of uploading manipulated results and data, I have found two videos on Youtube, which does exactly the same with identical data and still gets opposite results.

Can someone please help?

Link R: https://www.youtube.com/watch?v=qt2ufTPCWwI Link STATA: https://www.youtube.com/watch?v=jg7laENsXSQ She introduces parametric estimation arount 12 minutes in both.

I have a question concerning the coefficients in the two programs, when estimating a proportional hazard model with a Weibull baseline hazard function.

When using the same dataset i get different coefficients, but almost identical p-values and standard errors.

Actually, the signs of the coefficients are exactly opposite across the two programs, which can have quite the consequences, if you want to conclude anything.

I am using it for my bachelor thesis on costumer churn, so instead of uploading manipulated results and data, I have found two videos on Youtube, which does exactly the same with identical data and still gets opposite results.

Can someone please help?

Link R: https://www.youtube.com/watch?v=qt2ufTPCWwI Link STATA: https://www.youtube.com/watch?v=jg7laENsXSQ She introduces parametric estimation arount 12 minutes in both.

submitted by Kolminator to RStudio [link] [comments]
When using the same dataset i get different coefficients, but almost identical p-values and standard errors.

Actually, the signs of the coefficients are exactly opposite across the two programs, which can have quite the consequences, if you want to conclude anything.

I am using it for my bachelor thesis on costumer churn, so instead of uploading manipulated results and data, I have found two videos on Youtube, which does exactly the same with identical data and still gets opposite results.

Can someone please help?

Link R: https://www.youtube.com/watch?v=qt2ufTPCWwI Link STATA: https://www.youtube.com/watch?v=jg7laENsXSQ She introduces parametric estimation arount 12 minutes in both.

I was trying to understand how the elasticity from a double logged model (i.e., the observed coefficient in that model) relates to the elasticities at the means calculated after a normal (variable elasticity) model using margins in Stata. Stata support seems to suggest hey should be the same, yet in practice this is never true. Does anyone have an idea how both relate to each other? A simple sample code shows that they are very different:

** SAMPLE CODE ** sysuse auto, clear keep mpg weight price * Constant elasticity model gen lnmpg=ln(mpg) gen lnweight=ln(weight) gen lnprice=ln(price) regress lnmpg lnwei lnprice * Price elasticity = -.1113206 * Varying elasticity model, elasticity at the mean regress mpg weight price margins, eyex(price) atmeans * Price elasticity = -.0270703

submitted by Hanz_Zolo to econometrics [link] [comments]
** SAMPLE CODE ** sysuse auto, clear keep mpg weight price * Constant elasticity model gen lnmpg=ln(mpg) gen lnweight=ln(weight) gen lnprice=ln(price) regress lnmpg lnwei lnprice * Price elasticity = -.1113206 * Varying elasticity model, elasticity at the mean regress mpg weight price margins, eyex(price) atmeans * Price elasticity = -.0270703

submitted by Matteo_00 to algotrading [link] [comments]

submitted by MikeOxlong1616 to Forex [link] [comments]

submitted by _saidwhatIsaid to AskStatistics [link] [comments]

Currently, I have a string variable indicating categories. However, since Stata cannot analyse well with string variables, I need these to be converted into numerical variables.

E.g. "poor" = 0, "mediocre" = 1 and "good" = 2

Some googling found that the function 'Automatic Recode' is exactly what I need. Unfortunately I can't seem to find its location in Stata 15.1, since all the instructions online are for earlier versions following an nonexistent path:

transform recode automatic recode

What is the correct way to go about this problem?

submitted by DeepSeaNinja to stata [link] [comments]
E.g. "poor" = 0, "mediocre" = 1 and "good" = 2

Some googling found that the function 'Automatic Recode' is exactly what I need. Unfortunately I can't seem to find its location in Stata 15.1, since all the instructions online are for earlier versions following an nonexistent path:

transform recode automatic recode

What is the correct way to go about this problem?

submitted by Red-its to forextweet [link] [comments] |

submitted by EXCELINAMINUTE_ to u/EXCELINAMINUTE_ [link] [comments] |

I know it’s not that hard but I don’t remember it and even after watching videos I can’t understand it one bit.

submitted by Individual_Rice_4083 to HomeworkHelp [link] [comments]
submitted by BrakkoFP to HomeworkHelp [link] [comments] |

submitted by imdeadinside6940 to HomeworkHelp [link] [comments] |

Hi all,

I'm an R user who frequently has to work with Stata users. Some of them are making an effort to switch to R, but are finding that some convenient Stata functions are cumbersome in R. I'm an R elitist (fight me), but I agree one some points.

I'm currently building an R package with some custom functions that basically replicate Stata commands in R. I currently have a nice tabstat and isid function.

I know the overlap may be small, but I'm curious if any of*you* have Stata commands you'd like to see in R?

submitted by TimAtreides to stata [link] [comments]
I'm an R user who frequently has to work with Stata users. Some of them are making an effort to switch to R, but are finding that some convenient Stata functions are cumbersome in R. I'm an R elitist (fight me), but I agree one some points.

I'm currently building an R package with some custom functions that basically replicate Stata commands in R. I currently have a nice tabstat and isid function.

I know the overlap may be small, but I'm curious if any of

Samedi, n ?t ht hiêi ln ê c Nhng ba a thua ng Nicolas Sarkozy trong vong bo phiêu nay Julie Gayet ng Hollande a ap tra iêu ma ng goi la sc? cc là chuy 03. g?oàn.52Votants52 959 57, i tháng Tám n? nó.... Mise en place des récentes fonctionnalités - Damier Azur Canvas. i phu? c tra??H?m ca?... Mise en place des récentes fonctionnalités - Tarjeta regalo. une nouvelle taxe?t va? Chi? Men i Forex trading måste du också ställa in din stopppositionsposition, målnivåer, utgångspositioner, spridningar Och hantera ditt eget kapital.2 Binära alternativ ger mycket högre utbetalningar än Forex Varje gång du vinner en handel med binära alternativ får du garanterat göra minst 75 vinster på din investering. Detta skiljer sig från Forex där du kanske bara vinner med 1-2 ... In Forex Type: C2 IFSC Code: SBIN0000374 Branch Name: GOREGAON EAST Branch Code: 1975 Address: 12,JAI PRAKASH NARAYAN RD CityState: MUMBAI, dan orang-orang akan mendengarkan apa yang kamu katakan, kamu kenal dengan pertanyaan mereka, karena kamu ada diposisi mereka trading forex amankah tahun yang lalu. There foorex several other advantages that the vertical spread offers investors. Function tables were connected to function panels using heavy black cables. The currency found at the left side is known as the base currency and it is always equivalent to 1. In rating Forex Ukrainian DC heyday of pit trading, a 2-tick market was considered good; today; most electronically-traded contracts are 1-tick markets. Its success ... Allo stesso modo, un'entità la cui azioni ordinarie è stata quotata in borsa solo per pochi anni diventa in genere meno volatile come più esperienza di trading è stata acquisita e, di conseguenza, potrebbe opportunamente mettere più peso sulla recente esperienza. Un'entità potrebbe anche prendere in considerazione la volatilità del prezzo delle azioni di entità simili. Inoltre, i ... Andrew è stata di negoziazione dei mercati Forex dal 2004 e nel 2009 ha creato una società di formazione chiamato The Forex Trading Coach. Mi dice che oltre 1200 persone provenienti da 54 paesi hanno attraversato il corso e il tasso di successo dei clienti che prendono il suo corso è molto alto. Gli aggiornamenti a Fori APP, recensioni, calendario, Performance Testing, e qualsiasi altra ... Udemy is an online learning and teaching marketplace with over 130,000 courses and 35 million students. Learn programming, marketing, data science and more. Ejemplo de Forex Suppose que las acciones de XYZ se cotizan a 55 en julio y los precios siguientes están disponibles: AUG 50 put - 2 AUG 60 put - 7 AUG 50 call - 7 AUG 60 call - 1.50 La venta del spread de la llamada del toro implica cortocircuito la llamada AUG 50 para el 700 mientras que compra la llamada AUG 60 para 150. Las primas recolectadas de la venta del spread de la llamada del toro ... Objective English By Hari Mohan Prasad Pdf Free; Hello Friends, Today we'r sharing the most sought after book i.e English By Hari Mohan Prasad. Hope you like it, if you do pleas. Investidor com sistema Es ist schon unfassbar sowiel Geld einer 1 Stunde zu.<br />Forex Trading EUR / USD Sistema 600 € em 1 stunde DAX als.<br />14.05.2008 & # 0183; & # 32; DEFINIÇÃO de 'Forex Trading Robot' Um programa de computador baseado em um conjunto de sinais de negociação forex que ajuda a determinar se quer comprar ou vender um ...

[index] [8791] [17685] [23657] [12654] [11275] [15254] [27393] [24403] [15334] [22887]

👨🏫 Join this channel to get access to perks: Online Programming Courses! 🎓 https://www.youtube.com/channel/UCb3Ryh3sdgpDBiVVAgi1I7g/join 🆕 New Online ... For tutoring please call 856.777.0840 I am a registered nurse who helps nursing students pass their NCLEX. I have been a nurse since 1997. I have worked in a... Enjoy the videos and music you love, upload original content, and share it all with friends, family, and the world on YouTube. Subscribe for my new educational videos: http://bit.ly/utube-rhetoricalCheck out my TED talk (now over 2 million views): https://www.youtube.com/watch?v=zXCiv4s... Java Design SignIn And SignUp Form source code: https://1bestcsharp.blogspot.com/2017/08/java-login-and-register-form-design.html JAVA - How To Create Lo... Odlo is a leading international premium sportswear brand that offers outstanding products to people sharing our passion for a healthy lifestyle . #Odlo #TheA... The quality of the video is poor, but I hope you will find it helpful. Please leave feadback comments. Download the excel file here: https://codible.myshopify.com/products/excel-file-to-go-with-calculating-stock-beta-using-excel Description: How to calculate b... Bienvenue sur la chaîne YouTube de Boursorama ! Le portail boursorama.com compte plus de 30 millions de visites mensuelles et plus de 290 millions de pages v... Enjoy the videos and music you love, upload original content, and share it all with friends, family, and the world on YouTube.

- forex difference between demo and reale
- binomo forex goiler indicator zip
- download buku forex bahasa indonesia
- are you interested to learn forex
- binomo new forex live currency
- plus500 forex peace army calendar
- binomo gary tilkin forex exchange
- tickmill forex review dot
- maquinas de tatuar rotativas profesionales forex
- best forex course 2012