Autocorrelation, also known as serial correlation, may exist in a regression model when the order of the observations in the data is relevant or important. In other words, with time-series (and sometimes panel or logitudinal) data, autocorrelation is a concern.

Most of the CLRM assumptions that allow econometricians to prove the desirable properties of the OLS estimators (the Gauss-Markov theorem) directly involve characteristics of the error term. One of the CLRM assumptions deals with the relationship between values of the error term. Specifically, the CLRM assumes there’s no autocorrelation.

No autocorrelation refers to a situation in which no identifiable relationship exists between the values of the error term. Econometricians express no autocorrelation as

The figure shows the regression of a model satisfying the CLRM assumption of no autocorrelation. As you can see, when the error term exhibits no autocorrelation, the positive and negative error values are random.

When autocorrelation does occur, it takes either positive or negative form. Of course, autocorrelation can be incorrectly identified as well. The following sections explain how to distinguish between positive and negative correlation as well as how to avoid falsely stating that autocorrelation exists.

Positive versus negative autocorrelation

If autocorrelation is present, positive autocorrelation is the most likely outcome. Positive autocorrelation occurs when an error of a given sign tends to be followed by an error of the same sign. For example, positive errors are usually followed by positive errors, and negative errors are usually followed by negative errors.

.Self- taught.LabVIEW is a (massive) package. To expand.You’ve got - exactly - what you need.Essentially if you are running any experiment and want to save time/money. What is LabVIEW? Wiki definition: LabVIEW is a system-design platform and development. A guide to strengths and uses presented by Dummies.

Positive autocorrelation is expressed as

The positive autocorrelation depicted in the following figure is only one among several possible patterns. An error term with a sequencing of positive and negative error values usually indicates positive autocorrelation. Sequencing refers to a situation where most positive errors are followed or preceded by additional positive errors or when negative errors are followed or preceded by other negative errors.

Although unlikely, negative autocorrelation is also possible. Negative autocorrelation occurs when an error of a given sign tends to be followed by an error of the opposite sign. For instance, positive errors are usually followed by negative errors and negative errors are usually followed by positive errors.

Negative autocorrelation is expressed as

The following figure illustrates the typical pattern of negative autocorrelation. An error term with a switching of positive and negative error values usually indicates negative autocorrelation. A switching pattern is the opposite of sequencing, so most positive errors tend to be followed or preceded by negative errors and vice versa.

Whether you have positive or negative autocorrelation, in the presence of autocorrelation, the OLS estimators may not be efficient (that is, they may not achieve the smallest variance). In addition, the estimated standard errors of the coefficients are biased, which results in unreliable hypothesis tests (t-statistics). The OLS estimates, however, remain unbiased.

Misspecification and autocorrelation

When you’re drawing conclusions about autocorrelation using the error pattern, all other CLRM assumptions must hold, especially the assumption that the model is correctly specified. If a model isn’t correctly specified, you may mistakenly identify the model as suffering from autocorrelation.

Take a look at the following figure, which illustrates a scenario where the model has been inappropriately specified as linear when the relationship is nonlinear. The misspecification shown here would end up producing an error pattern that resembles positive autocorrelation.

Perform misspecification checks if there’s evidence of autocorrelation and you’re uncertain about the accuracy of the specification. Misspecification is a more serious issue than autocorrelation because you can’t prove the OLS estimators to be unbiased if the model isn’t correctly specified.

Introduction: How to Use UART in LabVIEW

For this project, I connected the PmodGPS (GPS module) to the chipKIT WF32 using LabVIEW and LabVIEW MakerHub LINX. This guide will go through how to set up the UART communication, what UART basically is, and how to convert readings from the device into useful information.

If you're interested in setting up your chipKIT WF32 or other supported board, check out this Instructable.

Use this as a guide to code your own UART devices using LabVIEW. This project can be done using the LabVIEW Physical Computing Kit which contains LabVIEW Home Bundle and chipKIT WF32.

Teacher Notes

Teachers! Did you use this instructable in your classroom?
Add a Teacher Note to share how you incorporated it into your lesson.

Step 1: Materials

1) LabVIEW

LabVIEW Home Bundle can be used for this project and is sold by Digilent. Otherwise, any LabVIEW version can be used including the free trial. Nissan ners software download.

2) chipKIT WF32

3) LabVIEW MakerHub LINX

FabFilter Total Bundle (Win) VST, Plugins, Audio, Samples, Free, Download. Fabfilter pro q 3 crack free download.

4) USB A to mini B USB cable

5) PmodGPS

6) Wires

Step 2: Download and Install LabVIEW and LINX

Use this instructable to figure out how to get started with LabVIEW MakerHub LINX. Note that LINX supports many other boards in addition to the chipKIT WF32. Here is the full list of supported devices.

Step 3: UART Setup

UART connections have 4 data channels: RTS 'Ready to Send', RX 'Receive', TX 'Transmit', and CTS 'Clear to Send'. The RX and TX lines are the ones that actually transmit and receive data so in most cases you can tie RTS and CTS to ground (or sometimes you can even leave them floating). There are also many UART connections that only have RX and TX connections.

An important thing to note about UART connections is that the RX from one board connects to the TX of the other and vice-versa. Now let's take a look at the PmodGPS data sheet here.

There are 6 connections to the PmodGPS. The first is labeled 3DF which indicates the status of the user's positional fix. When the module has a constant fix, the pin stays low and if the module is unable to get a fix then the pin will toggle every second. The second and third pins are the RX and TX lines that actually transmit the information to our board. Pin 4 is called 1PPS which drives the line high for 100ms then low for 900ms and repeats this process (honestly not sure what the point of it is). Then of course we have the ground and 3.3V lines to power the module.

Now that we know the connections, let's hook up the PmodGPS to the chipKIT WF32. The chipKIT WF32 uses UART0 to communicate with LabVIEW so we need to use UART1 (technically the data sheet calls this UART4 but there is a note about how UART4 is accessed using the runtime object Serial1). UART1 are pins 39 and 40. Pin 39 is is the RX channel and pin 40 is the TX channel.

Thus for the PmodGPS we need to connect 3DF and 1PPS to GPIO channels (if you want to read those pins) and we need to connect the RX channel on the PmodGPS to pin 40 on the WF32 and connect TX on the PmodGPS to pin 39 on the WF32. Also connect ground and 3.3V.

Step 4: LabVIEW Code

I created subVIs for the PmodGPS to make it easier to use. I have attached the subVIs below as well as the main example. There is an open VI, a read VI, and a close VI. Extract the zip file to somewhere on your computer. When opening the main VI called 'PmodGPS Example', LabVIEW will prompt you to find the three subVIs. Just browse to where you extracted the zip file and select the appropriate subVI.

The open VI is pictured above. It uses the LINX UART Open VI and sets the baud rate to 9600 since that is the baud rate that the PmodGPS runs on by default.

The close VI is also pictured above. It uses the LINX UART Close VI and terminates the connection to the PmodGPS.

Next let's go over how we read the values in greater detail.

Step 5: Convert Readings to Useful Information

Our UART connection is set up and now what we need to do is read the values from our GPS. From the PmodGPS data sheet, we see that it sends data in NMEA sentences. Check out this page to see what the different NMEA sentences are.

To start the read, the first thing we need to focus on is looking for bytes available at the port. Using the UART bytes available VI, we can see how many bytes are sitting in the serial buffer. We can then use the UART read (byte array) to read the serial data at the port as a byte array. Each letter or number sent via UART is in ASCII so if the number 0 is sent, the UART read will read 48 decimal which is 0 in ASCII.

We can use the byte array to string to convert the incoming byte array into the actual NMEA string. You probably have noticed some extra calculations and shift registers but those will be addressed later.

OK we have an NMEA transmission from the GPS. We'll move forward with the example NMEA sentence $GPGGA,123519,4807.038,N,01131.000,E,1,08,0.9,545.4,M,46.9,M,*47.

Our first while loop breaks the transmission by the new line character since each NMEA sentence ends with this. From here, the leftovers are removed and sent into a shift register to add onto the next transmission since that will contain the rest of the sentence.

The first 6 bytes of each broken apart sentence are read to see what data type we have. In this case we read $GPGGA so we send that to a case structure so that we can read the line correctly since not all lines contain the same information. All data is comma separated so we break all the data into multiple strings and then convert those strings to useful information. If you're interested in how I did the other lines, check out the NMEA sentences and the attached LabVIEW code.

Converting readings to useful information is by far the hardest part of UART. Try using this as an example/guide to code your own UART interfaces! If you have any questions, check out the LabVIEW MakerHub Forums.

Be the First to Share

Recommendations

• Trash to Treasure Contest

• Raspberry Pi Contest 2020

• Wearables Contest